neural network

Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics ICLR 2023 Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NeurIPS 2023 Optimization or Architecture: How to Hack Kalman Filtering NeurIPS 2023 Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method NeurIPS 2023 Origins of Low-Dimensional Adversarial Perturbations AISTATS 2023 Orion: Online Backdoor Sample Detection via Evolution Deviance IJCAI 2023 Out-of-Distribution Generalization by Neural-Symbolic Joint Training AAAI 2023 Overcoming catastrophic forgetting with classifier expander ACML 2023 Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability CVPR 2023 Overparameterized Random Feature Regression with Nearly Orthogonal Data AISTATS 2023 PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization NeurIPS 2023 Parameter-Level Soft-Masking for Continual Learning ICML 2023 Parametric Surface Constrained Upsampler Network for Point Cloud AAAI 2023 Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models ICML 2023 Partial Network Cloning CVPR 2023 PASS: Patch Automatic Skip Scheme for Efficient Real-Time Video Perception on Edge Devices AAAI 2023 PATS: Patch Area Transportation With Subdivision for Local Feature Matching CVPR 2023 PDP: Parameter-free Differentiable Pruning is All You Need NeurIPS 2023 PD-Quant: Post-Training Quantization Based on Prediction Difference Metric CVPR 2023 PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability AAAI 2023 Performative Prediction with Neural Networks AISTATS 2023 Permutation Equivariant Neural Functionals NeurIPS 2023 Perpetual Humanoid Control for Real-time Simulated Avatars ICCV 2023 Perspective Fields for Single Image Camera Calibration CVPR 2023 Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability NeurIPS 2023