{"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":"/task/parameter-estimation/papers/8","list_of":"/task/parameter-estimation","task":"parameter estimation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":8,"pages_in_order":18,"rows_per_page":100,"rows":[701,800],"of":1719,"counts":{"archive_papers_tagged":1719,"with_a_code_link":369,"where_syntology_ran_a_sample":53,"not_listed_spam_title":0,"listed":1719,"listed_where_code_ran":53,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":45,"every_run_a_failure_of_syntologys_instrument":8,"listed_with_a_run_with_no_instrument_failure":45,"listed_every_run_a_failure_of_syntologys_instrument":8,"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":"/task/parameter-estimation","prev":"/task/parameter-estimation/papers/7","next":"/task/parameter-estimation/papers/9","papers":[{"url":null,"slug":"efficient-cnn-lstm-based-parameter-estimation","title":"Efficient CNN-LSTM based Parameter Estimation of Levy Driven Stochastic Differential Equations","date":"2024-03-07","arxiv_id":"2403.04246","repositories_listed":0,"syntology":null},{"url":null,"slug":"dendrogram-of-mixing-measures-learning-latent","title":"Dendrogram of mixing measures: Hierarchical clustering and model selection for finite mixture models","date":"2024-03-04","arxiv_id":"2403.01684","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-radar-signal-detection-and-fft","title":"Automatic Radar Signal Detection and FFT Estimation using Deep Learning","date":"2024-02-29","arxiv_id":"2402.19073","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepemc-t2-mapping-deep-learning-enabled-t2","title":"DeepEMC-T2 Mapping: Deep Learning-Enabled T2 Mapping Based on Echo Modulation Curve Modeling","date":"2024-02-29","arxiv_id":"2402.19205","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonlinear-identification-algorithm-for-online","title":"Nonlinear identification algorithm for online and offline study of pulmonary mechanical ventilation","date":"2024-02-28","arxiv_id":"2402.18709","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer-based-parameter-estimation-in","title":"Transformer-based Parameter Estimation in Statistics","date":"2024-02-28","arxiv_id":"2403.00019","repositories_listed":0,"syntology":null},{"url":null,"slug":"capt-category-level-articulation-estimation","title":"CAPT: Category-level Articulation Estimation from a Single Point Cloud Using Transformer","date":"2024-02-27","arxiv_id":"2402.17360","repositories_listed":0,"syntology":null},{"url":null,"slug":"opening-cabinets-and-drawers-in-the-real","title":"Opening Articulated Structures in the Real World","date":"2024-02-27","arxiv_id":"2402.17767","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiable-particle-filtering-using","title":"Differentiable Particle Filtering using Optimal Placement Resampling","date":"2024-02-26","arxiv_id":"2402.16639","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-power-of-pure-attention","title":"Exploring the Power of Pure Attention Mechanisms in Blind Room Parameter Estimation","date":"2024-02-25","arxiv_id":"2402.16003","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-and-efficient-sequential-radar-parameter","title":"Fast and Efficient Sequential Radar Parameter Estimation in MIMO-OTFS Systems","date":"2024-02-22","arxiv_id":"2402.14612","repositories_listed":0,"syntology":null},{"url":null,"slug":"multistatic-ofdm-radar-fusion-of-music-based","title":"Multistatic OFDM Radar Fusion of MUSIC-based Angle Estimation","date":"2024-02-20","arxiv_id":"2402.13118","repositories_listed":0,"syntology":null},{"url":null,"slug":"autonomous-emergency-braking-with-driver-in","title":"Autonomous Emergency Braking With Driver-In-The-Loop: Torque Vectoring for Active Learning","date":"2024-02-16","arxiv_id":"2402.10761","repositories_listed":0,"syntology":null},{"url":null,"slug":"thompson-sampling-in-partially-observable","title":"Thompson Sampling in Partially Observable Contextual Bandits","date":"2024-02-15","arxiv_id":"2402.10289","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-statistical-model-of-bursty-mixed-gaussian","title":"A Statistical Model of Bursty Mixed Gaussian-impulsive Noise: Model and Parameter Estimation","date":"2024-02-09","arxiv_id":"2402.06395","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-model-for-membrane-degradation-using-a","title":"A model for membrane degradation using a gelatin invadopodia assay","date":"2024-02-08","arxiv_id":"2404.05730","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-parameter-estimation-in-deviated-gaussian","title":"On Parameter Estimation in Deviated Gaussian Mixture of Experts","date":"2024-02-07","arxiv_id":"2402.05220","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-passive-intelligent-reflecting-surface","title":"Semi-Passive Intelligent Reflecting Surface Enabled Sensing Systems","date":"2024-02-05","arxiv_id":"2402.03042","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-model-selection-within-the-matrix","title":"Data-driven model selection within the matrix completion method for causal panel data models","date":"2024-02-02","arxiv_id":"2402.01069","repositories_listed":0,"syntology":null},{"url":null,"slug":"spde-priors-for-uncertainty-quantification-of","title":"Neural variational Data Assimilation with Uncertainty Quantification using SPDE priors","date":"2024-02-02","arxiv_id":"2402.01855","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-crucial-parameter-for-rank-frequency","title":"A Crucial Parameter for Rank-Frequency Relation in Natural Languages","date":"2024-02-01","arxiv_id":"2402.00271","repositories_listed":0,"syntology":null},{"url":null,"slug":"tensor-based-process-control-and-monitoring","title":"Tensor-based process control and monitoring for semiconductor manufacturing with unstable disturbances","date":"2024-01-31","arxiv_id":"2401.17573","repositories_listed":0,"syntology":null},{"url":null,"slug":"cftm-continuous-time-fractional-topic-model","title":"CFTM: Continuous time fractional topic model","date":"2024-01-29","arxiv_id":"2402.01734","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-temperature-sample-efficient-for-softmax","title":"Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?","date":"2024-01-25","arxiv_id":"2401.13875","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-identification-of-nonseparable-1","title":"Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling","date":"2024-01-23","arxiv_id":"2401.12476","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-simulators-for-the","title":"Deep Learning Based Simulators for the Phosphorus Removal Process Control in Wastewater Treatment via Deep Reinforcement Learning Algorithms","date":"2024-01-23","arxiv_id":"2401.12822","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-room-geometry-inference-from-multichannel","title":"3D Room Geometry Inference from Multichannel Room Impulse Response using Deep Neural Network","date":"2024-01-19","arxiv_id":"2401.10453","repositories_listed":0,"syntology":null},{"url":null,"slug":"composite-learning-backstepping-control-with","title":"Composite learning backstepping control with guaranteed exponential stability and robustness","date":"2024-01-19","arxiv_id":"2401.10785","repositories_listed":0,"syntology":null},{"url":null,"slug":"homodyned-k-distribution-parameter-estimation-1","title":"Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches","date":"2024-01-19","arxiv_id":"2401.11006","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligent-optimization-and-machine-learning","title":"Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals","date":"2024-01-18","arxiv_id":"2401.10355","repositories_listed":0,"syntology":null},{"url":null,"slug":"power-grid-parameter-estimation-without-phase","title":"Power Grid Parameter Estimation Without Phase Measurements: Theory and Empirical Validation","date":"2024-01-18","arxiv_id":"2401.09989","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-tau-leap-for-simulating-chemical","title":"A hybrid tau-leap for simulating chemical kinetics with applications to parameter estimation","date":"2024-01-17","arxiv_id":"2401.09097","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalized-reference-signals-design-for","title":"OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing","date":"2024-01-17","arxiv_id":"2401.09643","repositories_listed":0,"syntology":null},{"url":null,"slug":"gans-for-evt-based-model-parameter-estimation","title":"GANs for EVT Based Model Parameter Estimation in Real-time Ultra-Reliable Communication","date":"2024-01-12","arxiv_id":"2401.10280","repositories_listed":0,"syntology":null},{"url":null,"slug":"modelling-open-source-software-reliability","title":"Modelling Open-Source Software Reliability Incorporating Swarm Intelligence-Based Techniques","date":"2024-01-05","arxiv_id":"2401.02664","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-the-hurst-parameter-of-linear","title":"Deep learning the Hurst parameter of linear fractional processes and assessing its reliability","date":"2024-01-03","arxiv_id":"2401.01789","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-equlibrium-inference-of-stochastic","title":"Out-of-equlibrium inference of feeding rates through population data from generic consumer-resource stochastic dynamics","date":"2024-01-03","arxiv_id":"2401.01632","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-parameter-estimation-of-sinusoidal","title":"On the Parameter Estimation of Sinusoidal Models for Speech and Audio Signals","date":"2024-01-02","arxiv_id":"2401.01255","repositories_listed":0,"syntology":null},{"url":null,"slug":"learned-trajectory-embedding-for-subspace","title":"Learned Trajectory Embedding for Subspace Clustering","date":"2024-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"acceleration-estimation-of-signal-propagation","title":"Acceleration Estimation of Signal Propagation Path Length Changes for Wireless Sensing","date":"2023-12-30","arxiv_id":"2401.00160","repositories_listed":0,"syntology":null},{"url":null,"slug":"camera-calibration-for-the-surround-view","title":"Camera calibration for the surround-view system: a benchmark and dataset","date":"2023-12-27","arxiv_id":"2312.16499","repositories_listed":0,"syntology":null},{"url":null,"slug":"instrumental-variables-based-drem-for-online","title":"Instrumental Variables based DREM for Online Asymptotic Identification of Perturbed Linear Systems","date":"2023-12-25","arxiv_id":"2312.15631","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-day-needs-based-modeling-approach-for","title":"A Multi-day Needs-based Modeling Approach for Activity and Travel Demand Analysis","date":"2023-12-24","arxiv_id":"2312.15373","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-inference-with-limited-memory-a","title":"Statistical Inference with Limited Memory: A Survey","date":"2023-12-23","arxiv_id":"2312.15225","repositories_listed":0,"syntology":null},{"url":null,"slug":"millimeter-wave-radio-slam-end-to-end","title":"Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation","date":"2023-12-21","arxiv_id":"2312.13741","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonlinear-moving-horizon-estimation-for","title":"Nonlinear moving horizon estimation for robust state and parameter estimation - extended version","date":"2023-12-20","arxiv_id":"2312.13175","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-target-two-way-integrated-sensing-and","title":"Multi-Target Two-way Integrated Sensing and Communications with Full Duplex MIMO Radios","date":"2023-12-16","arxiv_id":"2312.10345","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-inversion-of-gpr-waveforms-for","title":"Bayesian inversion of GPR waveforms for sub-surface material characterization: an uncertainty-aware retrieval of soil moisture and overlaying biomass properties","date":"2023-12-13","arxiv_id":"2312.07928","repositories_listed":0,"syntology":null},{"url":null,"slug":"convex-parameter-estimation-of-perturbed","title":"Convex Parameter Estimation of Perturbed Multivariate Generalized Gaussian Distributions","date":"2023-12-12","arxiv_id":"2312.07479","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-event-triggered-control-for-strict","title":"Adaptive Event-triggered Control For Strict-feedback Systems With Time-varying Parameters","date":"2023-12-11","arxiv_id":"2312.06178","repositories_listed":0,"syntology":null},{"url":null,"slug":"finite-sample-identification-of-continuous","title":"Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems","date":"2023-12-08","arxiv_id":"2312.05382","repositories_listed":0,"syntology":null},{"url":null,"slug":"rational-kriging","title":"Rational Kriging","date":"2023-12-08","arxiv_id":"2312.05372","repositories_listed":0,"syntology":null},{"url":null,"slug":"autoencoding-labeled-interpolator-inferring","title":"Autoencoding Labeled Interpolator, Inferring Parameters From Image, And Image From Parameters","date":"2023-12-07","arxiv_id":"2312.04640","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-fast-inference-of","title":"Deep Learning for Fast Inference of Mechanistic Models' Parameters","date":"2023-12-05","arxiv_id":"2312.03166","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimation-of-physical-parameters-of","title":"Artificial Neural Network for Estimation of Physical Parameters of Sea Water using LiDAR Waveforms","date":"2023-12-05","arxiv_id":"2312.10068","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometry-aware-normalizing-wasserstein-flows","title":"Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference","date":"2023-11-30","arxiv_id":"2311.18826","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-impact-of-sampling-on-deep-sequential","title":"On the Impact of Sampling on Deep Sequential State Estimation","date":"2023-11-28","arxiv_id":"2311.17006","repositories_listed":0,"syntology":null},{"url":null,"slug":"composite-adaptive-lyapunov-based-deep-neural","title":"Composite Adaptive Lyapunov-Based Deep Neural Network (Lb-DNN) Controller","date":"2023-11-21","arxiv_id":"2311.13056","repositories_listed":0,"syntology":null},{"url":null,"slug":"pinns-based-uncertainty-quantification-for","title":"PINNs-Based Uncertainty Quantification for Transient Stability Analysis","date":"2023-11-21","arxiv_id":"2311.12947","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimation-strategies-for-the-condition","title":"Estimation Strategies for the Condition Monitoring of a Battery Systemin a Hybrid Electric Vehicle","date":"2023-11-18","arxiv_id":"2311.11107","repositories_listed":0,"syntology":null},{"url":null,"slug":"femda-a-unified-framework-for-discriminant","title":"FEMDA: a unified framework for discriminant analysis","date":"2023-11-13","arxiv_id":"2311.07518","repositories_listed":0,"syntology":null},{"url":null,"slug":"unbiased-neural-networks-for-parameter","title":"Bias-Reduced Neural Networks for Parameter Estimation in Quantitative MRI","date":"2023-11-13","arxiv_id":"2312.11468","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-shape-prior-for-wrinkle-accurate","title":"Diffusion Shape Prior for Wrinkle-Accurate Cloth Registration","date":"2023-11-10","arxiv_id":"2311.05828","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-theoretic-generalization-bounds-7","title":"Information-theoretic generalization bounds for learning from quantum data","date":"2023-11-09","arxiv_id":"2311.05529","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-parameter-estimation-with-1","title":"Distributed Parameter Estimation with Gaussian Observation Noises in Time-varying Digraphs","date":"2023-11-07","arxiv_id":"2311.03911","repositories_listed":0,"syntology":null},{"url":null,"slug":"forward-kh-2-divergence-based-variational","title":"Forward $χ^2$ Divergence Based Variational Importance Sampling","date":"2023-11-04","arxiv_id":"2311.02516","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-cancer-progression-an-integrated","title":"Modeling Cancer Progression: An Integrated Workflow Extending Data-Driven Kinetic Models to Bio-Mechanical PDE Models","date":"2023-11-03","arxiv_id":"2311.02232","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-spde-solver-for-uncertainty","title":"Neural SPDE solver for uncertainty quantification in high-dimensional space-time dynamics","date":"2023-11-03","arxiv_id":"2311.01783","repositories_listed":0,"syntology":null},{"url":null,"slug":"nomopy-noise-modeling-in-python","title":"NoMoPy: Noise Modeling in Python","date":"2023-10-31","arxiv_id":"2311.00084","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-spectral-regularisation-framework-for","title":"A spectral regularisation framework for latent variable models designed for single channel applications","date":"2023-10-30","arxiv_id":"2310.19246","repositories_listed":0,"syntology":null},{"url":null,"slug":"transient-thermal-and-electrical","title":"Transient Thermal and Electrical Characteristics of a Cylindrical LiFeS2 Cell with Equivalent Circuit Model","date":"2023-10-28","arxiv_id":"2311.02095","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-true-beliefs-from-declared","title":"Estimating True Beliefs in Opinion Dynamics with Social Pressure","date":"2023-10-26","arxiv_id":"2310.17171","repositories_listed":0,"syntology":null},{"url":null,"slug":"mode-selection-and-target-classification-in","title":"Mode Selection and Target Classification in Cognitive Radar Networks","date":"2023-10-25","arxiv_id":"2310.17006","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-cpu-optimized-parameter-estimation","title":"Efficient CPU-Optimized Parameter Estimation for Modeling Fish Schooling Behavior in Large Particle Systems","date":"2023-10-24","arxiv_id":"2310.15753","repositories_listed":0,"syntology":null},{"url":null,"slug":"neuromorphic-sampling-of-sparse-signals","title":"Neuromorphic Sampling of Sparse Signals","date":"2023-10-24","arxiv_id":"2310.15750","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperparameter-optimization-of-hp-greedy","title":"Hyperparameter optimization of hp-greedy reduced basis for gravitational wave surrogates","date":"2023-10-23","arxiv_id":"2310.15143","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-theory-for-softmax-gating","title":"A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts","date":"2023-10-22","arxiv_id":"2310.14188","repositories_listed":0,"syntology":null},{"url":null,"slug":"electrical-fault-localisation-over-a","title":"Electrical Fault Localisation Over a Distributed Parameter Transmission Line","date":"2023-10-20","arxiv_id":"2310.13359","repositories_listed":0,"syntology":null},{"url":null,"slug":"v2x-sidelink-positioning-in-fr1-scenarios","title":"V2X Sidelink Positioning in FR1: Scenarios, Algorithms, and Performance Evaluation","date":"2023-10-20","arxiv_id":"2310.13753","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-stage-2d-channel-extrapolation-scheme","title":"A Two-Stage 2D Channel Extrapolation Scheme for TDD 5G NR Systems","date":"2023-10-13","arxiv_id":"2310.08851","repositories_listed":0,"syntology":null},{"url":null,"slug":"log-gaussian-gamma-processes-for-training","title":"Log-Gaussian Gamma Processes for Training Bayesian Neural Networks in Raman and CARS Spectroscopies","date":"2023-10-12","arxiv_id":"2310.08055","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-preserved-aggregate-thermal-dynamic","title":"Privacy-Preserved Aggregate Thermal Dynamic Model of Buildings","date":"2023-10-12","arxiv_id":"2310.08418","repositories_listed":0,"syntology":null},{"url":null,"slug":"better-and-simpler-lower-bounds-for","title":"Better and Simpler Lower Bounds for Differentially Private Statistical Estimation","date":"2023-10-10","arxiv_id":"2310.06289","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-stochastic-particle-variational-bayesian","title":"A Stochastic Particle Variational Bayesian Inference Inspired Deep-Unfolding Network for Non-Convex Parameter Estimation","date":"2023-10-09","arxiv_id":"2310.05382","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-data-driven-models-for-accurate","title":"Leveraging Data-Driven Models for Accurate Analysis of Grid-Tied Smart Inverters Dynamics","date":"2023-10-03","arxiv_id":"2310.02056","repositories_listed":0,"syntology":null},{"url":null,"slug":"hoh-markerless-multimodal-human-object-human","title":"HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count","date":"2023-10-01","arxiv_id":"2310.00723","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-rotation-averaging-revisited-and","title":"Incremental Rotation Averaging Revisited","date":"2023-09-29","arxiv_id":"2309.16924","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-static-parameter-estimation-in-the-near","title":"Multi-static Parameter Estimation in the Near/Far Field Beam Space for Integrated Sensing and Communication Applications","date":"2023-09-26","arxiv_id":"2309.14778","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-ris-phase-profile-design-and-power","title":"Joint RIS Phase Profile Design and Power Allocation for Parameter Estimation in Presence of Eavesdropping","date":"2023-09-25","arxiv_id":"2309.14280","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-perspective-of-top-k-sparse","title":"Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts","date":"2023-09-25","arxiv_id":"2309.13850","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-closer-look-at-parameter-identifiability","title":"A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth","date":"2023-09-23","arxiv_id":"2309.13319","repositories_listed":0,"syntology":null},{"url":null,"slug":"attention-is-all-you-need-for-blind-room","title":"Attention Is All You Need For Blind Room Volume Estimation","date":"2023-09-23","arxiv_id":"2309.13504","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-satellites-collaboration-for-joint","title":"Multiple Satellites Collaboration for Joint Code-aided CFOs and CPOs Estimation","date":"2023-09-22","arxiv_id":"2309.12828","repositories_listed":0,"syntology":null},{"url":null,"slug":"bloch-equation-enables-physics-informed","title":"Bloch Equation Enables Physics-informed Neural Network in Parametric Magnetic Resonance Imaging","date":"2023-09-21","arxiv_id":"2309.11763","repositories_listed":0,"syntology":null},{"url":null,"slug":"radyololet-radar-detection-and-parameter","title":"RadYOLOLet: Radar Detection and Parameter Estimation Using YOLO and WaveLet","date":"2023-09-21","arxiv_id":"2309.12094","repositories_listed":0,"syntology":null},{"url":null,"slug":"dive-deeper-into-rectifying-homography-for","title":"Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration","date":"2023-09-19","arxiv_id":"2309.10314","repositories_listed":0,"syntology":null},{"url":null,"slug":"cramer-rao-bound-optimization-for-active-ris","title":"Cramer-Rao Bound Optimization for Active RIS-Empowered ISAC Systems","date":"2023-09-17","arxiv_id":"2309.09207","repositories_listed":0,"syntology":null},{"url":null,"slug":"2309-06413","title":"On Computationally Efficient Learning of Exponential Family Distributions","date":"2023-09-12","arxiv_id":"2309.06413","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-lasso-a-unifying-approach-of-lasso-and","title":"Neural lasso: a unifying approach of lasso and neural networks","date":"2023-09-07","arxiv_id":"2309.03770","repositories_listed":0,"syntology":null},{"url":null,"slug":"transmission-matrix-parameter-estimation-of","title":"Transmission matrix parameter estimation of COVID-19 evolution with age compartments using ensemble-based data assimilation","date":"2023-09-06","arxiv_id":"2309.07146","repositories_listed":0,"syntology":null}],"record_sha256":"be4f7edcde2f331e0f56423baeced3df0368468971da75a72e984125c5feb755","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}