{"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/lstm/papers/15","list_of":"/method/lstm","method":"LSTM","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":15,"pages_in_order":55,"rows_per_page":100,"rows":[1401,1500],"of":5448,"counts":{"archive_papers_tagged":5448,"with_a_code_link":1823,"where_syntology_ran_a_sample":335,"not_listed_spam_title":0,"listed":5448,"listed_where_code_ran":335,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":283,"every_run_a_failure_of_syntologys_instrument":52,"listed_with_a_run_with_no_instrument_failure":283,"listed_every_run_a_failure_of_syntologys_instrument":52,"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/lstm","prev":"/method/lstm/papers/14","next":"/method/lstm/papers/16","papers":[{"paper":null,"slug":"detecting-driver-drowsiness-as-an-anomaly","title":"Detecting Driver Drowsiness as an Anomaly Using LSTM Autoencoders","date":"2022-09-12","arxiv_id":"2209.05269","n_code_links":0,"syntology":null},{"paper":"/paper/detecting-network-based-internet-censorship","slug":"detecting-network-based-internet-censorship","title":"Detecting Network-based Internet Censorship via Latent Feature Representation Learning","date":"2022-09-12","arxiv_id":"2209.05152","n_code_links":1,"syntology":null},{"paper":"/paper/poseit-a-visual-tactile-dataset-of-holding","slug":"poseit-a-visual-tactile-dataset-of-holding","title":"PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis","date":"2022-09-12","arxiv_id":"2209.05022","n_code_links":1,"syntology":null},{"paper":null,"slug":"multiple-object-tracking-in-recent-times-a","title":"Multiple Object Tracking in Recent Times: A Literature Review","date":"2022-09-11","arxiv_id":"2209.04796","n_code_links":0,"syntology":null},{"paper":null,"slug":"developing-a-multi-variate-prediction-model","title":"Developing a multi-variate prediction model for the detection of COVID-19 from Crowd-sourced Respiratory Voice Data","date":"2022-09-08","arxiv_id":"2209.03727","n_code_links":0,"syntology":null},{"paper":null,"slug":"impact-analysis-of-recovery-cases-due-to","title":"Impact analysis of recovery cases due to COVID19 using LSTM deep learning model","date":"2022-09-06","arxiv_id":"2209.02173","n_code_links":0,"syntology":null},{"paper":"/paper/modeling-user-repeat-consumption-behavior-for","slug":"modeling-user-repeat-consumption-behavior-for","title":"Modeling User Repeat Consumption Behavior for Online Novel Recommendation","date":"2022-09-05","arxiv_id":"2209.01963","n_code_links":1,"syntology":null},{"paper":null,"slug":"viecap4h-vlsp-2021-vietnamese-image","title":"vieCap4H-VLSP 2021: Vietnamese Image Captioning for Healthcare Domain using Swin Transformer and Attention-based LSTM","date":"2022-09-03","arxiv_id":"2209.01304","n_code_links":0,"syntology":null},{"paper":null,"slug":"vision-language-adaptive-mutual-decoder-for","title":"Vision-Language Adaptive Mutual Decoder for OOV-STR","date":"2022-09-02","arxiv_id":"2209.00859","n_code_links":0,"syntology":null},{"paper":"/paper/focus-driven-contrastive-learniang-for","slug":"focus-driven-contrastive-learniang-for","title":"Focus-Driven Contrastive Learniang for Medical Question Summarization","date":"2022-09-01","arxiv_id":"2209.00484","n_code_links":1,"syntology":null},{"paper":"/paper/negation-detection-in-dutch-clinical-texts-an","slug":"negation-detection-in-dutch-clinical-texts-an","title":"Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods","date":"2022-09-01","arxiv_id":"2209.00470","n_code_links":1,"syntology":null},{"paper":null,"slug":"recurrent-lstm-based-uav-trajectory","title":"Recurrent LSTM-based UAV Trajectory Prediction with ADS-B Information","date":"2022-09-01","arxiv_id":"2209.00436","n_code_links":0,"syntology":null},{"paper":"/paper/unified-fully-and-timestamp-supervised","slug":"unified-fully-and-timestamp-supervised","title":"Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation","date":"2022-09-01","arxiv_id":"2209.00638","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["boschresearch/uvast"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"classification-of-electroencephalograms","title":"Classification of Electroencephalograms during Mathematical Calculations Using Deep Learning","date":"2022-08-31","arxiv_id":"2209.00627","n_code_links":0,"syntology":null},{"paper":null,"slug":"group-activity-recognition-in-basketball","title":"Group Activity Recognition in Basketball Tracking Data -- Neural Embeddings in Team Sports (NETS)","date":"2022-08-31","arxiv_id":"2209.00451","n_code_links":0,"syntology":null},{"paper":null,"slug":"predict-stock-prices-with-arima-and-lstm","title":"Predict stock prices with ARIMA and LSTM","date":"2022-08-31","arxiv_id":"2209.02407","n_code_links":0,"syntology":null},{"paper":"/paper/denoising-architecture-for-unsupervised","slug":"denoising-architecture-for-unsupervised","title":"Denoising Architecture for Unsupervised Anomaly Detection in Time-Series","date":"2022-08-30","arxiv_id":"2208.14337","n_code_links":1,"syntology":null},{"paper":null,"slug":"digital-twin-assisted-risk-aware-sleep-mode","title":"Digital Twin Assisted Risk-Aware Sleep Mode Management Using Deep Q-Networks","date":"2022-08-30","arxiv_id":"2208.14380","n_code_links":0,"syntology":null},{"paper":null,"slug":"near-named-entity-and-attribute-recognition","title":"NEAR: Named Entity and Attribute Recognition of clinical concepts","date":"2022-08-30","arxiv_id":"2208.13949","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-language-agnostic-multilingual-streaming-on","title":"A Language Agnostic Multilingual Streaming On-Device ASR System","date":"2022-08-29","arxiv_id":"2208.13916","n_code_links":0,"syntology":null},{"paper":"/paper/deep-learning-based-sentiment-analysis-of","slug":"deep-learning-based-sentiment-analysis-of","title":"Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data","date":"2022-08-26","arxiv_id":"2209.12604","n_code_links":1,"syntology":null},{"paper":null,"slug":"static-seeding-and-clustering-of-lstm","title":"Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events","date":"2022-08-26","arxiv_id":"2208.12389","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-cnn-lstm-based-hybrid-deep-learning","title":"A CNN-LSTM-based hybrid deep learning approach to detect sentiment polarities on Monkeypox tweets","date":"2022-08-25","arxiv_id":"2208.12019","n_code_links":0,"syntology":null},{"paper":"/paper/a-study-on-broadcast-networks-for-music-genre","slug":"a-study-on-broadcast-networks-for-music-genre","title":"A Study on Broadcast Networks for Music Genre Classification","date":"2022-08-25","arxiv_id":"2208.12086","n_code_links":1,"syntology":null},{"paper":null,"slug":"predicting-query-item-relationship-using","title":"Predicting Query-Item Relationship using Adversarial Training and Robust Modeling Techniques","date":"2022-08-23","arxiv_id":"2208.10751","n_code_links":0,"syntology":null},{"paper":null,"slug":"query-response-interactions-by-multi-tasks-in","title":"Query-Response Interactions by Multi-tasks in Semantic Search for Chatbot Candidate Retrieval","date":"2022-08-23","arxiv_id":"2208.11018","n_code_links":0,"syntology":null},{"paper":"/paper/steducov-an-explored-and-benchmarked-dataset","slug":"steducov-an-explored-and-benchmarked-dataset","title":"StEduCov: An Explored and Benchmarked Dataset on Stance Detection in Tweets towards Online Education during COVID-19 Pandemic","date":"2022-08-22","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-tagging-of-knowledge-points-for-k12","title":"Automatic tagging of knowledge points for K12 math problems","date":"2022-08-21","arxiv_id":"2208.09867","n_code_links":0,"syntology":null},{"paper":null,"slug":"summarizing-patients-problems-from-hospital","title":"Summarizing Patients Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models","date":"2022-08-17","arxiv_id":"2208.08408","n_code_links":0,"syntology":null},{"paper":null,"slug":"quantum-machine-learning-for-material","title":"Quantum Machine Learning for Material Synthesis and Hardware Security","date":"2022-08-16","arxiv_id":"2208.08273","n_code_links":0,"syntology":null},{"paper":null,"slug":"text-difficulty-study-do-machines-behave-the","title":"Text Difficulty Study: Do machines behave the same as humans regarding text difficulty?","date":"2022-08-14","arxiv_id":"2208.14509","n_code_links":0,"syntology":null},{"paper":"/paper/adan-adaptive-nesterov-momentum-algorithm-for","slug":"adan-adaptive-nesterov-momentum-algorithm-for","title":"Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models","date":"2022-08-13","arxiv_id":"2208.06677","n_code_links":9,"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":["sail-sg/adan"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"building-a-chatbot-on-a-closed-domain-using","title":"Building a Chatbot on a Closed Domain using RASA","date":"2022-08-12","arxiv_id":"2208.06104","n_code_links":0,"syntology":null},{"paper":null,"slug":"facial-expression-recognition-and-image","title":"Facial Expression Recognition and Image Description Generation in Vietnamese","date":"2022-08-12","arxiv_id":"2208.06117","n_code_links":0,"syntology":null},{"paper":null,"slug":"assessing-the-unitary-rnn-as-an-end-to-end","title":"Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax","date":"2022-08-11","arxiv_id":"2208.05719","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-point-processes-using-recurrent","title":"Learning Point Processes using Recurrent Graph Network","date":"2022-08-11","arxiv_id":"2208.05736","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-lifelong-learning-of-recurrent-neural","title":"Towards lifelong learning of Recurrent Neural Networks for control design","date":"2022-08-08","arxiv_id":"2208.03980","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-algorithmically-generated-domains","title":"Detecting Algorithmically Generated Domains Using a GCNN-LSTM Hybrid Neural Network","date":"2022-08-06","arxiv_id":"2208.03445","n_code_links":0,"syntology":null},{"paper":null,"slug":"prediction-based-hybrid-slicing-framework-for","title":"Prediction-based Hybrid Slicing Framework for Service Level Agreement Guarantee in Mobility Scenarios: A Deep Learning Approach","date":"2022-08-06","arxiv_id":"2208.03460","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-solution-of-deep-learning-for","title":"A novel solution of deep learning for enhanced support vector machine for predicting the onset of type 2 diabetes","date":"2022-08-05","arxiv_id":"2208.06354","n_code_links":0,"syntology":null},{"paper":null,"slug":"model-blending-for-text-classification","title":"Model Blending for Text Classification","date":"2022-08-05","arxiv_id":"2208.02819","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-fidelity-surrogate-modeling-using-long","title":"Multi-fidelity surrogate modeling using long short-term memory networks","date":"2022-08-05","arxiv_id":"2208.03115","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-representation-modeling-based-language-gan","title":"InitialGAN: A Language GAN with Completely Random Initialization","date":"2022-08-04","arxiv_id":"2208.02531","n_code_links":0,"syntology":null},{"paper":null,"slug":"atp-a-holistic-attention-integrated-approach","title":"ATP: A holistic attention integrated approach to enhance ABSA","date":"2022-08-04","arxiv_id":"2208.02653","n_code_links":0,"syntology":null},{"paper":"/paper/tokyo-kion-on-query-based-generative","slug":"tokyo-kion-on-query-based-generative","title":"Tokyo Kion-On: Query-Based Generative Sonification of Atmospheric Data","date":"2022-08-04","arxiv_id":"2208.02494","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-novel-approach-to-network-intrusion","title":"A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach","date":"2022-08-03","arxiv_id":"2208.02094","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-study-on-covid-19-fake-news","title":"A Comparative Study on COVID-19 Fake News Detection Using Different Transformer Based Models","date":"2022-08-02","arxiv_id":"2208.01355","n_code_links":0,"syntology":null},{"paper":"/paper/alexatm-20b-few-shot-learning-using-a-large","slug":"alexatm-20b-few-shot-learning-using-a-large","title":"AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model","date":"2022-08-02","arxiv_id":"2208.01448","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"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":null}},{"paper":null,"slug":"global-attention-based-encoder-decoder-lstm","title":"Global Attention-based Encoder-Decoder LSTM Model for Temperature Prediction of Permanent Magnet Synchronous Motors","date":"2022-07-30","arxiv_id":"2208.00293","n_code_links":0,"syntology":null},{"paper":null,"slug":"end-to-end-view-synthesis-via-nerf-attention","title":"End-to-end View Synthesis via NeRF Attention","date":"2022-07-29","arxiv_id":"2207.14741","n_code_links":0,"syntology":null},{"paper":"/paper/explain-my-surprise-learning-efficient-long","slug":"explain-my-surprise-learning-efficient-long","title":"Explain My Surprise: Learning Efficient Long-Term Memory by Predicting Uncertain Outcomes","date":"2022-07-27","arxiv_id":"2207.13649","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-data-driven-method-for-multi-step","title":"A Data Driven Method for Multi-step Prediction of Ship Roll Motion in High Sea States","date":"2022-07-26","arxiv_id":"2207.12673","n_code_links":0,"syntology":null},{"paper":null,"slug":"estimating-value-at-risk-lstm-vs-garch","title":"Estimating value at risk: LSTM vs. GARCH","date":"2022-07-21","arxiv_id":"2207.10539","n_code_links":0,"syntology":null},{"paper":null,"slug":"mqretnn-multi-horizon-time-series-forecasting","title":"MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation","date":"2022-07-21","arxiv_id":"2207.10517","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequence-models-for-drone-vs-bird","title":"Sequence Models for Drone vs Bird Classification","date":"2022-07-21","arxiv_id":"2207.10409","n_code_links":0,"syntology":null},{"paper":"/paper/the-birth-of-bias-a-case-study-on-the-1","slug":"the-birth-of-bias-a-case-study-on-the-1","title":"The Birth of Bias: A case study on the evolution of gender bias in an English language model","date":"2022-07-21","arxiv_id":"2207.10245","n_code_links":1,"syntology":null},{"paper":"/paper/a-deep-learning-framework-for-wind-turbine","slug":"a-deep-learning-framework-for-wind-turbine","title":"A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms","date":"2022-07-19","arxiv_id":"2207.09457","n_code_links":1,"syntology":null},{"paper":"/paper/emotion-recognition-based-on-multi-task","slug":"emotion-recognition-based-on-multi-task","title":"Multi-Task Learning Framework for Emotion Recognition in-the-wild","date":"2022-07-19","arxiv_id":"2207.09373","n_code_links":1,"syntology":null},{"paper":"/paper/investigation-of-deep-learning-models-on","slug":"investigation-of-deep-learning-models-on","title":"Investigation of deep learning models on identification of minimum signal length for precise classification of conveyor rubber belt loads","date":"2022-07-19","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-sequence-models-for-text-classification","title":"Deep Sequence Models for Text Classification Tasks","date":"2022-07-18","arxiv_id":"2207.08880","n_code_links":0,"syntology":null},{"paper":null,"slug":"troll-tweet-detection-using-contextualized","title":"A Context-Sensitive Word Embedding Approach for The Detection of Troll Tweets","date":"2022-07-17","arxiv_id":"2207.08230","n_code_links":0,"syntology":null},{"paper":null,"slug":"nfdlm-a-lightweight-network-flow-based-deep","title":"NFDLM: A Lightweight Network Flow based Deep Learning Model for DDoS Attack Detection in IoT Domains","date":"2022-07-15","arxiv_id":"2207.10803","n_code_links":0,"syntology":null},{"paper":null,"slug":"strict-baselines-for-covid-19-forecasting-and","title":"Strict baselines for Covid-19 forecasting and ML perspective for USA and Russia","date":"2022-07-15","arxiv_id":"2207.07689","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-methods-for-protein-family","title":"Deep Learning Methods for Protein Family Classification on PDB Sequencing Data","date":"2022-07-14","arxiv_id":"2207.06678","n_code_links":0,"syntology":null},{"paper":"/paper/a-general-contextualized-rewriting-framework","slug":"a-general-contextualized-rewriting-framework","title":"A General Contextualized Rewriting Framework for Text Summarization","date":"2022-07-13","arxiv_id":"2207.05948","n_code_links":1,"syntology":null},{"paper":"/paper/diverse-dance-synthesis-via-keyframes-with","slug":"diverse-dance-synthesis-via-keyframes-with","title":"Diverse Dance Synthesis via Keyframes with Transformer Controllers","date":"2022-07-13","arxiv_id":"2207.05906","n_code_links":1,"syntology":null},{"paper":"/paper/multi-modal-depression-estimation-based-on","slug":"multi-modal-depression-estimation-based-on","title":"Multi-modal Depression Estimation based on Sub-attentional Fusion","date":"2022-07-13","arxiv_id":"2207.06180","n_code_links":1,"syntology":null},{"paper":null,"slug":"unsupervised-hebbian-learning-on-point-sets","title":"Unsupervised Hebbian Learning on Point Sets in StarCraft II","date":"2022-07-13","arxiv_id":"2207.12323","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-transformer-model-with-pre-layer","title":"Deep Transformer Model with Pre-Layer Normalization for COVID-19 Growth Prediction","date":"2022-07-10","arxiv_id":"2207.06356","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-path-attention-is-all-you-need-for-audio","title":"Dual-Path Cross-Modal Attention for better Audio-Visual Speech Extraction","date":"2022-07-09","arxiv_id":"2207.04213","n_code_links":0,"syntology":null},{"paper":null,"slug":"neural-language-models-are-not-born-equal-to","title":"Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps","date":"2022-07-07","arxiv_id":"2207.03380","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-optimal-solutions-via-an-lstm","title":"Learning Optimal Solutions via an LSTM-Optimization Framework","date":"2022-07-06","arxiv_id":"2207.02937","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-cross-corpus-study-on-speech-emotion","title":"A cross-corpus study on speech emotion recognition","date":"2022-07-05","arxiv_id":"2207.02104","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-for-short-term-instant-energy","title":"Deep Learning for Short-term Instant Energy Consumption Forecasting in the Manufacturing Sector","date":"2022-07-04","arxiv_id":"2207.01595","n_code_links":0,"syntology":null},{"paper":null,"slug":"spatiotemporal-feature-learning-based-on-two","title":"Spatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scans","date":"2022-07-04","arxiv_id":"2207.01579","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-aiot-enabled-autonomous-dementia","title":"An AIoT-enabled Autonomous Dementia Monitoring System","date":"2022-07-02","arxiv_id":"2207.00804","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-the-explainers-black-box","slug":"evaluating-the-explainers-black-box","title":"Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs","date":"2022-07-01","arxiv_id":"2207.00551","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["epfl-ml4ed/evaluating-explainers"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"literature-on-hand-gesture-recognition-using","title":"Literature on Hand GESTURE Recognition using Graph based methods","date":"2022-07-01","arxiv_id":"2207.00329","n_code_links":0,"syntology":null},{"paper":null,"slug":"advances-in-prediction-of-readmission-rates","title":"Advances in Prediction of Readmission Rates Using Long Term Short Term Memory Networks on Healthcare Insurance Data","date":"2022-06-30","arxiv_id":"2207.00066","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-synthesis-of-neurons-for-recurrent","title":"Automatic Synthesis of Neurons for Recurrent Neural Nets","date":"2022-06-29","arxiv_id":"2207.03577","n_code_links":0,"syntology":null},{"paper":"/paper/ddktor-automatic-diadochokinetic-speech","slug":"ddktor-automatic-diadochokinetic-speech","title":"DDKtor: Automatic Diadochokinetic Speech Analysis","date":"2022-06-29","arxiv_id":"2206.14639","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-prediction-network-architecture-in-rnn","title":"On the Prediction Network Architecture in RNN-T for ASR","date":"2022-06-29","arxiv_id":"2206.14618","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-universality-of-the-volatility","title":"On the universality of the volatility formation process: when machine learning and rough volatility agree","date":"2022-06-28","arxiv_id":"2206.14114","n_code_links":0,"syntology":null},{"paper":"/paper/improving-clinical-efficiency-and-reducing","slug":"improving-clinical-efficiency-and-reducing","title":"Improving Clinical Efficiency and Reducing Medical Errors through NLP-enabled diagnosis of Health Conditions from Transcription Reports","date":"2022-06-27","arxiv_id":"2206.13516","n_code_links":1,"syntology":null},{"paper":null,"slug":"explainable-and-high-performance-hate-and","title":"Explainable and High-Performance Hate and Offensive Speech Detection","date":"2022-06-26","arxiv_id":"2206.12983","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-comparison-of-encoders-for-attention-based","title":"On Comparison of Encoders for Attention based End to End Speech Recognition in Standalone and Rescoring Mode","date":"2022-06-26","arxiv_id":"2206.12829","n_code_links":0,"syntology":null},{"paper":null,"slug":"video-anomaly-detection-via-prediction","title":"Video Anomaly Detection via Prediction Network with Enhanced Spatio-Temporal Memory Exchange","date":"2022-06-26","arxiv_id":"2206.12914","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multi-model-based-deep-learning-framework","title":"A multi-model-based deep learning framework for short text multiclass classification with the imbalanced and extremely small data set","date":"2022-06-24","arxiv_id":"2206.12027","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-approach-for-analysis-of-distributed","title":"An Intensity and Phase Stacked Analysis of Phase-OTDR System using Deep Transfer Learning and Recurrent Neural Networks","date":"2022-06-24","arxiv_id":"2206.12484","n_code_links":0,"syntology":null},{"paper":null,"slug":"confidence-score-based-conformer-speaker","title":"Confidence Score Based Conformer Speaker Adaptation for Speech Recognition","date":"2022-06-24","arxiv_id":"2206.12045","n_code_links":0,"syntology":null},{"paper":"/paper/ml-based-approach-for-nfl-defensive-pass","slug":"ml-based-approach-for-nfl-defensive-pass","title":"ML-Based Approach for NFL Defensive Pass Interference Prediction Using GPS Tracking Data","date":"2022-06-24","arxiv_id":"2206.13222","n_code_links":1,"syntology":null},{"paper":null,"slug":"lbdmids-lstm-based-deep-learning-model-for","title":"LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks","date":"2022-06-23","arxiv_id":"2207.00424","n_code_links":0,"syntology":null},{"paper":"/paper/the-muse-2022-multimodal-sentiment-analysis","slug":"the-muse-2022-multimodal-sentiment-analysis","title":"The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress","date":"2022-06-23","arxiv_id":"2207.05691","n_code_links":1,"syntology":null},{"paper":"/paper/an-open-source-and-reproducible","slug":"an-open-source-and-reproducible","title":"An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series Forecasting","date":"2022-06-22","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/envpool-a-highly-parallel-reinforcement","slug":"envpool-a-highly-parallel-reinforcement","title":"EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine","date":"2022-06-21","arxiv_id":"2206.10558","n_code_links":3,"syntology":{"ran":5,"of":5,"n_ran_checked":4,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["sail-sg/envpool"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["named_in_paper","official"]}}},{"paper":null,"slug":"knowda-all-in-one-knowledge-mixture-model-for","title":"KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP","date":"2022-06-21","arxiv_id":"2206.10265","n_code_links":0,"syntology":null},{"paper":null,"slug":"gait-cycle-reconstruction-and-human","title":"Gait Cycle Reconstruction and Human Identification from Occluded Sequences","date":"2022-06-20","arxiv_id":"2206.13395","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-machine-learning-approach-to-predicting-1","title":"A machine learning approach to predicting pore pressure response in liquefiable sands under cyclic loading","date":"2022-06-15","arxiv_id":"2206.07780","n_code_links":0,"syntology":null},{"paper":null,"slug":"text-generation-with-text-editing-models","title":"Text Generation with Text-Editing Models","date":"2022-06-14","arxiv_id":"2206.07043","n_code_links":0,"syntology":null},{"paper":null,"slug":"grounding-in-social-media-an-approach-to","title":"Grounding in social media: An approach to building a chit-chat dialogue model","date":"2022-06-12","arxiv_id":"2206.05696","n_code_links":0,"syntology":null}],"record_sha256":"47ee1441d504264dc9dddbd18d71fd3b5b74b3d8ba669dd83c81761027741e66","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}