| PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction | Dec 31, 2019 | Generalization BoundsLearning Theory | CodeCode Available | 1 | 5 |
| DDIM sampling for Generative AIBIM, a faster intelligent structural design framework | Dec 30, 2024 | DenoisingLearning Theory | CodeCode Available | 1 | 5 |
| Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization | Aug 11, 2020 | BIG-bench Machine LearningLearning Theory | CodeCode Available | 1 | 5 |
| A Comprehensive Survey of Continual Learning: Theory, Method and Application | Jan 31, 2023 | Continual LearningLearning Theory | CodeCode Available | 1 | 5 |
| Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method | Sep 29, 2024 | Federated LearningLearning Theory | CodeCode Available | 1 | 5 |
| A Semantic Change Detection Network Based on Boundary Detection and Task Interaction for High-Resolution Remote Sensing Images | May 26, 2025 | Boundary DetectionChange Detection | CodeCode Available | 1 | 5 |
| Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks | Dec 13, 2023 | Learning Theory | CodeCode Available | 1 | 5 |
| Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic Segmentation | Mar 12, 2024 | Learning TheorySemantic Segmentation | CodeCode Available | 1 | 5 |
| Foreseeing the Benefits of Incidental Supervision | Jun 9, 2020 | InformativenessLearning Theory | CodeCode Available | 0 | 5 |
| A Brain-inspired Algorithm for Training Highly Sparse Neural Networks | Mar 17, 2019 | Learning Theory | CodeCode Available | 0 | 5 |
| Estimating the Local Learning Coefficient at Scale | Feb 6, 2024 | Learning Theory | CodeCode Available | 0 | 5 |
| Generalization Bounds with Data-dependent Fractal Dimensions | Feb 6, 2023 | Generalization BoundsLearning Theory | CodeCode Available | 0 | 5 |
| Efficient Training for Positive Unlabeled Learning | Aug 24, 2016 | Learning Theory | CodeCode Available | 0 | 5 |
| Double descent in quantum machine learning | Jan 17, 2025 | Learning TheoryQuantum Machine Learning | CodeCode Available | 0 | 5 |
| End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data | Sep 26, 2024 | Learning Theory | CodeCode Available | 0 | 5 |
| Learning invariant representations of time-homogeneous stochastic dynamical systems | Jul 19, 2023 | Learning Theory | CodeCode Available | 0 | 5 |
| Deep Learning with CNNs: A Compact Holistic Tutorial with Focus on Supervised Regression (Preprint) | Aug 22, 2024 | ArticlesDeep Learning | CodeCode Available | 0 | 5 |
| A Bayesian Perspective of Statistical Machine Learning for Big Data | Nov 9, 2018 | BIG-bench Machine LearningGaussian Processes | CodeCode Available | 0 | 5 |
| Deep Learning without Poor Local Minima | May 23, 2016 | Deep LearningLearning Theory | CodeCode Available | 0 | 5 |
| Generalization in Machine Learning via Analytical Learning Theory | Feb 21, 2018 | BIG-bench Machine LearningDeep Learning | CodeCode Available | 0 | 5 |
| Data-Error Scaling in Machine Learning on Natural Discrete Combinatorial Mutation-prone Sets: Case Studies on Peptides and Small Molecules | May 8, 2024 | Learning Theory | CodeCode Available | 0 | 5 |
| Deep Active Learning with Augmentation-based Consistency Estimation | Nov 5, 2020 | Active LearningData Augmentation | CodeCode Available | 0 | 5 |
| Continuous vs. Discrete Optimization of Deep Neural Networks | Jul 14, 2021 | Computational EfficiencyDeep Learning | CodeCode Available | 0 | 5 |
| Consistent Sparse Deep Learning: Theory and Computation | Feb 25, 2021 | Deep LearningGeneralization Bounds | CodeCode Available | 0 | 5 |
| Data-Driven Performance Guarantees for Classical and Learned Optimizers | Apr 22, 2024 | Learning TheoryMeta-Learning | CodeCode Available | 0 | 5 |
