{"total":72,"rows":[{"id":"2205.13147","title":"Matryoshka Representation Learning","created":"2022-05-26","cited_by_count":282,"area":null},{"id":"2103.11511","title":"MoViNets: Mobile Video Networks for Efficient Video Recognition","created":"2021-03-21","cited_by_count":135,"area":null},{"id":"2101.05544","title":"DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation","created":"2021-01-14","cited_by_count":48,"area":null},{"id":"2404.06351","title":"HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention","created":"2024-04-09","cited_by_count":38,"area":null},{"id":"2104.08277","title":"Divide-and-Conquer for Lane-Aware Diverse Trajectory Prediction","created":"2021-04-16","cited_by_count":37,"area":null},{"id":"2103.05271","title":"Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation","created":"2021-03-09","cited_by_count":35,"area":null},{"id":"2110.13786","title":"Diversity and Generalization in Neural Network Ensembles","created":"2021-10-26","cited_by_count":32,"area":null},{"id":"2103.16848","title":"Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding","created":"2021-03-31","cited_by_count":29,"area":null},{"id":"2112.07431","title":"Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation","created":"2021-12-14","cited_by_count":29,"area":null},{"id":"2204.05859","title":"Bootstrap Motion Forecasting With Self-Consistent Constraints","created":"2022-04-12","cited_by_count":23,"area":null},{"id":"2109.12622","title":"Using Soft Labels to Model Uncertainty in Medical Image Segmentation","created":"2021-09-26","cited_by_count":18,"area":null},{"id":"2110.13740","title":"DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples","created":"2021-10-26","cited_by_count":18,"area":null},{"id":"2202.03898","title":"Verification-Aided Deep Ensemble Selection","created":"2022-02-08","cited_by_count":18,"area":null},{"id":"2104.11861","title":"Class-Incremental Experience Replay for Continual Learning under Concept Drift","created":"2021-04-24","cited_by_count":17,"area":null},{"id":"2207.00170","title":"TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction","created":"2022-06-30","cited_by_count":14,"area":null},{"id":"2303.15850","title":"That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation","created":"2023-03-28","cited_by_count":13,"area":null},{"id":"2311.01052","title":"Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis","created":"2023-11-02","cited_by_count":12,"area":null},{"id":"2407.15580","title":"Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing","created":"2024-07-22","cited_by_count":12,"area":null},{"id":"2107.07260","title":"MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators","created":"2021-07-15","cited_by_count":11,"area":null},{"id":"2303.00732","title":"R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents","created":"2023-03-01","cited_by_count":10,"area":null},{"id":"2509.19975","title":"From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting","created":"2025-09-24","cited_by_count":10,"area":null},{"id":"2303.13123","title":"Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification","created":"2023-03-23","cited_by_count":9,"area":null},{"id":"2307.10586","title":"A Holistic Assessment of the Reliability of Machine Learning Systems","created":"2023-07-20","cited_by_count":9,"area":null},{"id":"2301.06629","title":"Diverse Multimedia Layout Generation with Multi Choice Learning","created":"2023-01-16","cited_by_count":8,"area":null},{"id":"2207.09086","title":"MHR-Net: Multiple-Hypothesis Reconstruction of Non-Rigid Shapes from 2D Views","created":"2022-07-19","cited_by_count":7,"area":null},{"id":"2301.00141","title":"Self-Activating Neural Ensembles for Continual Reinforcement Learning","created":"2022-12-31","cited_by_count":7,"area":null},{"id":"2305.07845","title":"Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data","created":"2023-05-13","cited_by_count":7,"area":null},{"id":"2411.11911","title":"ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling","created":"2024-11-17","cited_by_count":7,"area":null},{"id":"2312.06386","title":"ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation","created":"2023-12-11","cited_by_count":6,"area":null},{"id":"2406.04706","title":"Winner-takes-all learners are geometry-aware conditional density estimators","created":"2024-06-07","cited_by_count":6,"area":null},{"id":"2406.14422","title":"FutureNet-LOF: Joint Trajectory Prediction and Lane Occupancy Field Prediction with Future Context Encoding","created":"2024-06-20","cited_by_count":6,"area":null},{"id":"2408.07507","title":"Decoder ensembling for learned latent geometries","created":"2024-08-14","cited_by_count":6,"area":null},{"id":"2508.12709","title":"MATPAC++: Enhanced Masked Latent Prediction for Self-Supervised Audio Representation Learning","created":"2025-08-18","cited_by_count":6,"area":null},{"id":"2208.04043","title":"SLiDE: Self-supervised LiDAR De-snowing through Reconstruction Difficulty","created":"2022-08-08","cited_by_count":5,"area":null},{"id":"2112.06693","title":"Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels","created":"2021-12-13","cited_by_count":4,"area":null},{"id":"2403.17678","title":"Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting","created":"2024-03-26","cited_by_count":4,"area":null},{"id":"2405.15719","title":"Hierarchical Uncertainty Exploration via Feedforward Posterior Trees","created":"2024-05-24","cited_by_count":4,"area":null},{"id":"2406.10455","title":"CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference","created":"2024-06-15","cited_by_count":4,"area":null},{"id":"2409.11172","title":"Annealed Winner-Takes-All for Motion Forecasting","created":"2024-09-17","cited_by_count":4,"area":null},{"id":"2506.05515","title":"Winner-takes-all for Multivariate Probabilistic Time Series Forecasting","created":"2025-06-05","cited_by_count":4,"area":null},{"id":"2607.27372","title":"Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation","created":"2026-07-29","cited_by_count":4,"area":null},{"id":"2311.04512","title":"FFINet: Future Feedback Interaction Network for Motion Forecasting","created":"2023-11-08","cited_by_count":3,"area":null},{"id":"2411.18497","title":"Multiple Choice Learning for Efficient Speech Separation with Many Speakers","created":"2024-11-27","cited_by_count":3,"area":null},{"id":"2511.18539","title":"TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting","created":"2025-11-23","cited_by_count":3,"area":null},{"id":"2104.00177","title":"Visual Attention in Imaginative Agents","created":"2021-04-01","cited_by_count":2,"area":null},{"id":"2212.00601","title":"Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters","created":"2022-12-01","cited_by_count":2,"area":null},{"id":"2505.20414","title":"RetroMotion: Retrocausal Motion Forecasting Models are Instructable","created":"2025-05-26","cited_by_count":2,"area":null},{"id":"2507.10419","title":"Multiple Choice Learning of Low-Rank Adapters for Language Modeling","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2605.29565","title":"From General Vision to Reliable Traversability Estimation: Adapting Vision Foundation Models for Unstructured Outdoor Environments","created":"2026-05-28","cited_by_count":2,"area":null},{"id":"2212.04831","title":"Uncertainty Estimation in Deep Speech Enhancement Using Complex Gaussian Mixture Models","created":"2022-12-09","cited_by_count":1,"area":null},{"id":"2212.07070","title":"Deep Negative Correlation Classification","created":"2022-12-14","cited_by_count":1,"area":null},{"id":"2303.02484","title":"Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries","created":"2023-03-04","cited_by_count":1,"area":null},{"id":"2309.00781","title":"Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction","created":"2023-09-02","cited_by_count":1,"area":null},{"id":"2312.11735","title":"Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions","created":"2023-12-18","cited_by_count":1,"area":null},{"id":"2407.16367","title":"Navigating Uncertainty in Medical Image Segmentation","created":"2024-07-23","cited_by_count":1,"area":null},{"id":"2410.19606","title":"Multi-modal Motion Prediction using Temporal Ensembling with Learning-based Aggregation","created":"2024-10-25","cited_by_count":1,"area":null},{"id":"2504.06591","title":"NAPER: Fault Protection for Real-Time Resource-Constrained Deep Neural Networks","created":"2025-04-09","cited_by_count":1,"area":null},{"id":"2507.01308","title":"LANet: A Lane Boundaries-Aware Approach For Robust Trajectory Prediction","created":"2025-07-02","cited_by_count":1,"area":null},{"id":"2108.02949","title":"Auxiliary Class Based Multiple Choice Learning","created":"2021-08-06","cited_by_count":0,"area":null},{"id":"2403.09749","title":"Towards Diverse Perspective Learning with Selection over Multiple Temporal Poolings","created":"2024-03-14","cited_by_count":0,"area":null},{"id":"2411.13026","title":"X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2502.07151","title":"Conditional Distribution Quantization in Machine Learning","created":"2025-02-11","cited_by_count":0,"area":null},{"id":"2504.07301","title":"CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression","created":"2025-04-09","cited_by_count":0,"area":null},{"id":"2507.06531","title":"ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture","created":"2025-07-09","cited_by_count":0,"area":null},{"id":"2511.17941","title":"V2X-RECT: An Efficient V2X Trajectory Prediction Framework via Redundant Interaction Filtering and Tracking Error Correction","created":"2025-11-22","cited_by_count":0,"area":null},{"id":"2603.20191","title":"Deterministic Mode Proposals: An Efficient Alternative to Generative Sampling for Ambiguous Segmentation","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2603.20232","title":"Fusing Driver Perceived and Physical Risk for Safety Critical Scenario Screening in Autonomous Driving","created":"2026-03-07","cited_by_count":0,"area":null},{"id":"2605.01346","title":"CHASE: Competing Hypotheses for Ambiguity-Aware Selective Prediction","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2607.05240","title":"Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing","created":"2026-07-06","cited_by_count":0,"area":null},{"id":"2608.03521","title":"Pivot-Centric Trajectory Prediction: Bridging Long Horizons via Dynamical Guidance","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.05423","title":"Why the Third Axis Is Freedom","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2610.01934","title":"Learning to Predict Distributions over Weight Updates for Test-Time Adaptation","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}