{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/kaiming-initialization/papers/9","list_of":"/method/kaiming-initialization","method":"Kaiming Initialization","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":9,"pages_in_order":30,"rows_per_page":100,"rows":[801,900],"of":2931,"counts":{"archive_papers_tagged":2931,"with_a_code_link":1332,"where_syntology_ran_a_sample":379,"not_listed_spam_title":0,"listed":2931,"listed_where_code_ran":379,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":319,"every_run_a_failure_of_syntologys_instrument":60,"listed_with_a_run_with_no_instrument_failure":319,"listed_every_run_a_failure_of_syntologys_instrument":60,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/kaiming-initialization","prev":"/method/kaiming-initialization/papers/8","next":"/method/kaiming-initialization/papers/10","papers":[{"paper":"/paper/marginalia-and-machine-learning-handwritten","slug":"marginalia-and-machine-learning-handwritten","title":"Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and Recognition","date":"2023-03-10","arxiv_id":"2303.05929","n_code_links":2,"syntology":null},{"paper":null,"slug":"an-evaluation-of-non-contrastive-self","title":"An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis","date":"2023-03-09","arxiv_id":"2303.05556","n_code_links":0,"syntology":null},{"paper":"/paper/a-comparative-study-of-deep-learning-and","slug":"a-comparative-study-of-deep-learning-and","title":"A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems","date":"2023-03-07","arxiv_id":"2303.03678","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-computer-vision-enabled-damage-detection","title":"A Computer Vision Enabled damage detection model with improved YOLOv5 based on Transformer Prediction Head","date":"2023-03-07","arxiv_id":"2303.04275","n_code_links":0,"syntology":null},{"paper":null,"slug":"filter-pruning-based-on-information-capacity","title":"Filter Pruning based on Information Capacity and Independence","date":"2023-03-07","arxiv_id":"2303.03645","n_code_links":0,"syntology":null},{"paper":null,"slug":"discrepancies-among-pre-trained-deep-neural","title":"Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability","date":"2023-03-05","arxiv_id":"2303.02551","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-based-convolutional-neural-network-3","title":"Attention-based convolutional neural network for perfusion T2-weighted MR images preprocessing","date":"2023-03-04","arxiv_id":"2303.02518","n_code_links":0,"syntology":null},{"paper":"/paper/extended-agriculture-vision-an-extension-of-a","slug":"extended-agriculture-vision-an-extension-of-a","title":"Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis","date":"2023-03-04","arxiv_id":"2303.02460","n_code_links":1,"syntology":null},{"paper":"/paper/benchmarking-white-blood-cell-classification","slug":"benchmarking-white-blood-cell-classification","title":"Benchmarking White Blood Cell Classification Under Domain Shift","date":"2023-03-03","arxiv_id":"2303.01777","n_code_links":1,"syntology":null},{"paper":"/paper/contrastive-hierarchical-clustering","slug":"contrastive-hierarchical-clustering","title":"Contrastive Hierarchical Clustering","date":"2023-03-03","arxiv_id":"2303.03389","n_code_links":1,"syntology":null},{"paper":"/paper/revisiting-adversarial-training-for-imagenet-1","slug":"revisiting-adversarial-training-for-imagenet-1","title":"Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models","date":"2023-03-03","arxiv_id":"2303.01870","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["nmndeep/revisiting-at"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/towards-democratizing-joint-embedding-self","slug":"towards-democratizing-joint-embedding-self","title":"Towards Democratizing Joint-Embedding Self-Supervised Learning","date":"2023-03-03","arxiv_id":"2303.01986","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/ffcv-ssl"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/unified-perception-efficient-video-panoptic","slug":"unified-perception-efficient-video-panoptic","title":"Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs","date":"2023-03-03","arxiv_id":"2303.01991","n_code_links":0,"syntology":null},{"paper":null,"slug":"speeding-up-efficientnet-selecting-update","title":"Speeding Up EfficientNet: Selecting Update Blocks of Convolutional Neural Networks using Genetic Algorithm in Transfer Learning","date":"2023-03-01","arxiv_id":"2303.00261","n_code_links":0,"syntology":null},{"paper":"/paper/deep-learning-for-identifying-iran-s-cultural","slug":"deep-learning-for-identifying-iran-s-cultural","title":"Deep Learning for Identifying Iran's Cultural Heritage Buildings in Need of Conservation Using Image Classification and Grad-CAM","date":"2023-02-28","arxiv_id":"2302.14354","n_code_links":1,"syntology":null},{"paper":null,"slug":"predicting-the-performance-of-a-computing","title":"Predicting the Performance of a Computing System with Deep Networks","date":"2023-02-27","arxiv_id":"2302.13638","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-light-weight-deep-learning-model-for-remote","title":"A Light-weight Deep Learning Model for Remote Sensing Image Classification","date":"2023-02-25","arxiv_id":"2302.13028","n_code_links":0,"syntology":null},{"paper":"/paper/amortised-invariance-learning-for-contrastive","slug":"amortised-invariance-learning-for-contrastive","title":"Amortised Invariance Learning for Contrastive Self-Supervision","date":"2023-02-24","arxiv_id":"2302.12712","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"0 ran · 2 unverified","official":{"repos":["ruchikachavhan/amortized-invariance-learning-ssl"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":"/paper/magnification-invariant-medical-image","slug":"magnification-invariant-medical-image","title":"Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers","date":"2023-02-22","arxiv_id":"2302.11488","n_code_links":0,"syntology":null},{"paper":null,"slug":"effects-of-architectures-on-continual","title":"Effects of Architectures on Continual Semantic Segmentation","date":"2023-02-21","arxiv_id":"2302.10718","n_code_links":0,"syntology":null},{"paper":null,"slug":"augmenting-endometriosis-analysis-from","title":"Augmenting endometriosis analysis from ultrasound data with deep learning","date":"2023-02-19","arxiv_id":"2302.09621","n_code_links":0,"syntology":null},{"paper":null,"slug":"gradient-based-wang-landau-algorithm-a-novel","title":"Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space","date":"2023-02-19","arxiv_id":"2302.09484","n_code_links":0,"syntology":null},{"paper":"/paper/meta-style-adversarial-training-for-cross","slug":"meta-style-adversarial-training-for-cross","title":"StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning","date":"2023-02-18","arxiv_id":"2302.09309","n_code_links":2,"syntology":null},{"paper":"/paper/qarv-quantization-aware-resnet-vae-for-lossy","slug":"qarv-quantization-aware-resnet-vae-for-lossy","title":"QARV: Quantization-Aware ResNet VAE for Lossy Image Compression","date":"2023-02-16","arxiv_id":"2302.08899","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["gitlab.com/viper-purdue/qarv-release"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["named_in_paper"]}}},{"paper":"/paper/cholectriplet2022-show-me-a-tool-and-tell-me","slug":"cholectriplet2022-show-me-a-tool-and-tell-me","title":"CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection","date":"2023-02-13","arxiv_id":"2302.06294","n_code_links":2,"syntology":null},{"paper":"/paper/implications-of-the-convergence-of-language","slug":"implications-of-the-convergence-of-language","title":"Do Vision and Language Models Share Concepts? A Vector Space Alignment Study","date":"2023-02-13","arxiv_id":"2302.06555","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["jiaangli/vlca"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/self-supervised-pseudo-colorizing-of-masked","slug":"self-supervised-pseudo-colorizing-of-masked","title":"Self-supervised pseudo-colorizing of masked cells","date":"2023-02-12","arxiv_id":"2302.05968","n_code_links":2,"syntology":null},{"paper":null,"slug":"an-efficient-instance-segmentation-approach","title":"An Efficient Instance Segmentation Approach for Extracting Fission Gas Bubbles on U-10Zr Annular Fuel","date":"2023-02-08","arxiv_id":"2302.12833","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-zero-shot-classification-with","slug":"boosting-zero-shot-classification-with","title":"Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable Diffusion","date":"2023-02-07","arxiv_id":"2302.03298","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["jordan-hs/diversity_is_definitely_needed"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"lut-nn-towards-unified-neural-network","title":"LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup","date":"2023-02-07","arxiv_id":"2302.03213","n_code_links":0,"syntology":null},{"paper":null,"slug":"hyphen-a-hybrid-packing-method-and","title":"HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks","date":"2023-02-05","arxiv_id":"2302.02407","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-suppressing-range-of-adaptive-stepsizes-of","title":"On Suppressing Range of Adaptive Stepsizes of Adam to Improve Generalisation Performance","date":"2023-02-02","arxiv_id":"2302.01029","n_code_links":0,"syntology":null},{"paper":"/paper/resilient-binary-neural-network","slug":"resilient-binary-neural-network","title":"Resilient Binary Neural Network","date":"2023-02-02","arxiv_id":"2302.00956","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["stevetsui/rebnn"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/adaptive-search-and-training-for-robust-and","slug":"adaptive-search-and-training-for-robust-and","title":"Adaptive Search-and-Training for Robust and Efficient Network Pruning","date":"2023-02-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/cross-modal-information-fusion-for-voice","slug":"cross-modal-information-fusion-for-voice","title":"Cross-modal information fusion for voice spoofing detection","date":"2023-02-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"qlab-quadratic-loss-approximation-based","title":"QLABGrad: a Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning","date":"2023-02-01","arxiv_id":"2302.00252","n_code_links":0,"syntology":null},{"paper":"/paper/nasiam-efficient-representation-learning","slug":"nasiam-efficient-representation-learning","title":"NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese Networks","date":"2023-01-31","arxiv_id":"2302.00059","n_code_links":1,"syntology":null},{"paper":"/paper/benchmarking-optimality-of-time-series","slug":"benchmarking-optimality-of-time-series","title":"Benchmarking optimality of time series classification methods in distinguishing diffusions","date":"2023-01-30","arxiv_id":"2301.13112","n_code_links":1,"syntology":null},{"paper":"/paper/depgraph-towards-any-structural-pruning","slug":"depgraph-towards-any-structural-pruning","title":"DepGraph: Towards Any Structural Pruning","date":"2023-01-30","arxiv_id":"2301.12900","n_code_links":1,"syntology":{"ran":7,"of":7,"n_ran_checked":7,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["VainF/Torch-Pruning"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/towards-verifying-the-geometric-robustness-of","slug":"towards-verifying-the-geometric-robustness-of","title":"Towards Verifying the Geometric Robustness of Large-scale Neural Networks","date":"2023-01-29","arxiv_id":"2301.12456","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["trustai/georobust"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"deciphering-the-projection-head","title":"Deciphering the Projection Head: Representation Evaluation Self-supervised Learning","date":"2023-01-28","arxiv_id":"2301.12189","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-external-knowledge-for-accurate","title":"Exploring External Knowledge for Accurate modeling of Visual and Language Problems","date":"2023-01-27","arxiv_id":"2302.08901","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-1x1-convolutions-can-we-train-cnns","title":"The Power of Linear Combinations: Learning with Random Convolutions","date":"2023-01-26","arxiv_id":"2301.11360","n_code_links":0,"syntology":null},{"paper":"/paper/trainable-activations-for-image","slug":"trainable-activations-for-image","title":"Trainable Activations for Image Classification","date":"2023-01-26","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/model-soups-to-increase-inference-without","slug":"model-soups-to-increase-inference-without","title":"Model soups to increase inference without increasing compute time","date":"2023-01-24","arxiv_id":"2301.10092","n_code_links":1,"syntology":null},{"paper":"/paper/read-the-signs-towards-invariance-to-gradient","slug":"read-the-signs-towards-invariance-to-gradient","title":"Read the Signs: Towards Invariance to Gradient Descent's Hyperparameter Initialization","date":"2023-01-24","arxiv_id":"2301.10133","n_code_links":1,"syntology":null},{"paper":"/paper/classification-of-luminal-subtypes-in-full","slug":"classification-of-luminal-subtypes-in-full","title":"Classification of Luminal Subtypes in Full Mammogram Images Using Transfer Learning","date":"2023-01-23","arxiv_id":"2301.09282","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-to-linearize-deep-neural-networks","title":"Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference","date":"2023-01-23","arxiv_id":"2301.09254","n_code_links":0,"syntology":null},{"paper":"/paper/local-window-attention-transformer-for","slug":"local-window-attention-transformer-for","title":"Local Window Attention Transformer for Polarimetric SAR Image Classification","date":"2023-01-23","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/sharp-eyes-a-salient-object-detector-working","slug":"sharp-eyes-a-salient-object-detector-working","title":"Sharp Eyes: A Salient Object Detector Working The Same Way as Human Visual Characteristics","date":"2023-01-18","arxiv_id":"2301.07431","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-2-uav-application-aware-content-and-network","title":"A$^2$-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems","date":"2023-01-16","arxiv_id":"2301.06363","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-side-tuning-for-document","slug":"multimodal-side-tuning-for-document","title":"Multimodal Side-Tuning for Document Classification","date":"2023-01-16","arxiv_id":"2301.07502","n_code_links":1,"syntology":null},{"paper":null,"slug":"lb-simtsc-an-efficient-similarity-aware-graph","title":"LB-SimTSC: An Efficient Similarity-Aware Graph Neural Network for Semi-Supervised Time Series Classification","date":"2023-01-12","arxiv_id":"2301.04838","n_code_links":0,"syntology":null},{"paper":"/paper/semppl-predicting-pseudo-labels-for-better","slug":"semppl-predicting-pseudo-labels-for-better","title":"SemPPL: Predicting pseudo-labels for better contrastive representations","date":"2023-01-12","arxiv_id":"2301.05158","n_code_links":2,"syntology":{"ran":12,"of":16,"n_ran_checked":12,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["deepmind/semppl","google-deepmind/semppl"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"deep-residual-axial-networks","title":"Deep Residual Axial Networks","date":"2023-01-11","arxiv_id":"2301.04631","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-resnet-image-classification","title":"Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication","date":"2023-01-11","arxiv_id":"2301.04623","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-for-classification-of-chest-x","title":"Deep Learning For Classification Of Chest X-Ray Images (Covid 19)","date":"2023-01-06","arxiv_id":"2301.02468","n_code_links":0,"syntology":null},{"paper":null,"slug":"groma-a-tool-for-measuring-deep-neural","title":"gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks","date":"2023-01-05","arxiv_id":"2301.02288","n_code_links":0,"syntology":null},{"paper":null,"slug":"training-trajectories-mini-batch-losses-and","title":"Training trajectories, mini-batch losses and the curious role of the learning rate","date":"2023-01-05","arxiv_id":"2301.02312","n_code_links":0,"syntology":null},{"paper":null,"slug":"conscious-brain-mind-controlled-cybonthitic","title":"A Novel Power-optimized CMOS sEMG Device with Ultra Low-noise integrated with ConvNet (VGG16) for Biomedical Applications","date":"2023-01-04","arxiv_id":"2301.09570","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-performance-in-neural-networks-by","title":"Increasing biases can be more efficient than increasing weights","date":"2023-01-03","arxiv_id":"2301.00924","n_code_links":0,"syntology":null},{"paper":"/paper/poincare-resnet-1","slug":"poincare-resnet-1","title":"Poincare ResNet","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"toplight-lightweight-neural-networks-with","title":"TOPLight: Lightweight Neural Networks With Task-Oriented Pretraining for Visible-Infrared Recognition","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/viewnet-a-novel-projection-based-backbone","slug":"viewnet-a-novel-projection-based-backbone","title":"ViewNet: A Novel Projection-Based Backbone With View Pooling for Few-Shot Point Cloud Classification","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/chest-x-ray-images-classification-with-cnn","slug":"chest-x-ray-images-classification-with-cnn","title":"Chest X-Ray Images Classification with CNN","date":"2022-12-31","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"a-comparison-study-of-deep-cnn-architecture","title":"A Comparison Study of Deep CNN Architecture in Detecting of Pneumonia","date":"2022-12-30","arxiv_id":"2212.14744","n_code_links":0,"syntology":null},{"paper":null,"slug":"myi-net-fully-automatic-detection-and","title":"MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images","date":"2022-12-28","arxiv_id":"2212.13715","n_code_links":0,"syntology":null},{"paper":null,"slug":"human-activity-recognition-from-wi-fi-csi","title":"Human Activity Recognition from Wi-Fi CSI Data Using Principal Component-Based Wavelet CNN","date":"2022-12-26","arxiv_id":"2212.13161","n_code_links":0,"syntology":null},{"paper":null,"slug":"frequency-regularization-for-improving","title":"Frequency Regularization for Improving Adversarial Robustness","date":"2022-12-24","arxiv_id":"2212.12732","n_code_links":0,"syntology":null},{"paper":null,"slug":"linear-features-segmentation-from-aerial","title":"Linear features segmentation from aerial images","date":"2022-12-23","arxiv_id":"2212.12327","n_code_links":0,"syntology":null},{"paper":null,"slug":"offline-clustering-approach-to-self","title":"Offline Clustering Approach to Self-supervised Learning for Class-imbalanced Image Data","date":"2022-12-22","arxiv_id":"2212.11444","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-and-improving-the-role-of","title":"Understanding and Improving the Role of Projection Head in Self-Supervised Learning","date":"2022-12-22","arxiv_id":"2212.11491","n_code_links":0,"syntology":null},{"paper":null,"slug":"moquad-motion-focused-quadruple-construction","title":"MoQuad: Motion-focused Quadruple Construction for Video Contrastive Learning","date":"2022-12-21","arxiv_id":"2212.10870","n_code_links":0,"syntology":null},{"paper":null,"slug":"covid-19-detection-based-on-self-supervised","title":"COVID-19 Detection Based on Self-Supervised Transfer Learning Using Chest X-Ray Images","date":"2022-12-19","arxiv_id":"2212.09276","n_code_links":0,"syntology":null},{"paper":"/paper/bort-towards-explainable-neural-networks-with","slug":"bort-towards-explainable-neural-networks-with","title":"Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint","date":"2022-12-18","arxiv_id":"2212.09062","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["zbr17/bort"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"improving-unsupervised-video-object","title":"Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy","date":"2022-12-17","arxiv_id":"2212.08816","n_code_links":0,"syntology":null},{"paper":null,"slug":"pre-trained-image-encoder-for-generalizable","title":"Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning","date":"2022-12-17","arxiv_id":"2212.08860","n_code_links":0,"syntology":null},{"paper":null,"slug":"dqnet-cross-model-detail-querying-for","title":"DQnet: Cross-Model Detail Querying for Camouflaged Object Detection","date":"2022-12-16","arxiv_id":"2212.08296","n_code_links":0,"syntology":null},{"paper":null,"slug":"combating-uncertainty-and-class-imbalance-in","title":"Combating Uncertainty and Class Imbalance in Facial Expression Recognition","date":"2022-12-15","arxiv_id":"2212.07751","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-ensemble-method-to-automatically-grade","title":"An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images","date":"2022-12-12","arxiv_id":"2212.06265","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-an-interpretation-of-resnets-via-solution","title":"On an Interpretation of ResNets via Solution Constructions","date":"2022-12-12","arxiv_id":"2212.05663","n_code_links":0,"syntology":null},{"paper":null,"slug":"error-aware-quantization-through-noise","title":"Error-aware Quantization through Noise Tempering","date":"2022-12-11","arxiv_id":"2212.05603","n_code_links":0,"syntology":null},{"paper":"/paper/an-ai-powered-vvpat-counter-for-elections-in","slug":"an-ai-powered-vvpat-counter-for-elections-in","title":"An AI-Powered VVPAT Counter for Elections in India","date":"2022-12-09","arxiv_id":"2212.11124","n_code_links":1,"syntology":null},{"paper":null,"slug":"ap-selective-activation-for-de-sparsifying","title":"AP: Selective Activation for De-sparsifying Pruned Neural Networks","date":"2022-12-09","arxiv_id":"2212.06145","n_code_links":0,"syntology":null},{"paper":null,"slug":"eeg-next-a-modernized-convnet-for-the","title":"EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG","date":"2022-12-08","arxiv_id":"2212.04951","n_code_links":0,"syntology":null},{"paper":"/paper/diffusioninst-diffusion-model-for-instance","slug":"diffusioninst-diffusion-model-for-instance","title":"DiffusionInst: Diffusion Model for Instance Segmentation","date":"2022-12-06","arxiv_id":"2212.02773","n_code_links":2,"syntology":{"ran":12,"of":16,"n_ran_checked":7,"n_instrument":5,"unverified":4,"pointer_only":7,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 3 honoured, 0 violated, 4 with no contract checked; 5 where Syntology's instrument failed) · 4 unverified","official":{"repos":["chenhaoxing/DiffusionInst"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"paper":"/paper/from-cnns-to-shift-invariant-twin-wavelet","slug":"from-cnns-to-shift-invariant-twin-wavelet","title":"From CNNs to Shift-Invariant Twin Models Based on Complex Wavelets","date":"2022-12-01","arxiv_id":"2212.00394","n_code_links":1,"syntology":null},{"paper":null,"slug":"resnet-structure-simplification-with-the","title":"ResNet Structure Simplification with the Convolutional Kernel Redundancy Measure","date":"2022-12-01","arxiv_id":"2212.00272","n_code_links":0,"syntology":null},{"paper":"/paper/euro-espnet-unsupervised-asr-open-source","slug":"euro-espnet-unsupervised-asr-open-source","title":"EURO: ESPnet Unsupervised ASR Open-source Toolkit","date":"2022-11-30","arxiv_id":"2211.17196","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["espnet/espnet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/gennape-towards-generalized-neural","slug":"gennape-towards-generalized-neural","title":"GENNAPE: Towards Generalized Neural Architecture Performance Estimators","date":"2022-11-30","arxiv_id":"2211.17226","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["Ascend-Research/GENNAPE"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"optimizing-explanations-by-network","title":"Optimizing Explanations by Network Canonization and Hyperparameter Search","date":"2022-11-30","arxiv_id":"2211.17174","n_code_links":0,"syntology":null},{"paper":null,"slug":"explaining-deep-convolutional-neural-networks-2","title":"Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations","date":"2022-11-28","arxiv_id":"2211.15143","n_code_links":0,"syntology":null},{"paper":null,"slug":"learnable-front-ends-based-on-temporal","title":"Learnable Front Ends Based on Temporal Modulation for Music Tagging","date":"2022-11-28","arxiv_id":"2211.15254","n_code_links":0,"syntology":null},{"paper":null,"slug":"synthetic-low-field-mri-super-resolution-via","title":"Synthetic Low-Field MRI Super-Resolution Via Nested U-Net Architecture","date":"2022-11-28","arxiv_id":"2211.15047","n_code_links":0,"syntology":null},{"paper":"/paper/a-knowledge-based-learning-framework-for-self","slug":"a-knowledge-based-learning-framework-for-self","title":"A Knowledge-based Learning Framework for Self-supervised Pre-training Towards Enhanced Recognition of Biomedical Microscopy Images","date":"2022-11-27","arxiv_id":"2211.14715","n_code_links":1,"syntology":null},{"paper":"/paper/unsupervised-wildfire-change-detection-based","slug":"unsupervised-wildfire-change-detection-based","title":"Unsupervised Wildfire Change Detection based on Contrastive Learning","date":"2022-11-26","arxiv_id":"2211.14654","n_code_links":1,"syntology":null},{"paper":null,"slug":"overcoming-catastrophic-forgetting-by-xai","title":"Overcoming Catastrophic Forgetting by XAI","date":"2022-11-25","arxiv_id":"2211.14177","n_code_links":0,"syntology":null},{"paper":null,"slug":"augop-inject-transformation-into-neural","title":"AugOp: Inject Transformation into Neural Operator","date":"2022-11-23","arxiv_id":"2211.12514","n_code_links":0,"syntology":null},{"paper":"/paper/global-temporal-difference-network-for-action","slug":"global-temporal-difference-network-for-action","title":"Global Temporal Difference Network for Action Recognition","date":"2022-11-23","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/one-eye-is-all-you-need-lightweight-ensembles","slug":"one-eye-is-all-you-need-lightweight-ensembles","title":"One Eye is All You Need: Lightweight Ensembles for Gaze Estimation with Single Encoders","date":"2022-11-22","arxiv_id":"2211.11936","n_code_links":1,"syntology":null}],"record_sha256":"0b19fcbff124ed0a21fb69305266ac24dcae1cba3e851464cdbc4925dac7640d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}