natural gradient

A Natural-Gradient Approach for Nonlinear Stochastic Systems with Parameter Uncertainty AAAI 2026 A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equation JMLR 2026 Beyond Euclidean Gossip: KL-Barycentric Consensus on Heterogeneous and Imbalanced Images CVPR 2026 Enhancing the Transferability of Jailbreak Attacks on Large Language Models via Exploiting Reparameterization Invariance ACL 2026 Learning to Infer Fast by Attending to Sparse Temporal Observations UAI 2026 ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning ICLR 2025 CAMEx: Curvature-aware Merging of Experts ICLR 2025 Near-optimal Sketchy Natural Gradients for Physics-Informed Neural Networks ICML 2025 On the Natural Gradient of the Evidence Lower Bound JMLR 2025 Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient NeurIPS 2024 Bayesian Online Natural Gradient (BONG) NeurIPS 2024 Fearless Stochasticity in Expectation Propagation NeurIPS 2024 Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NeurIPS 2024 Optimising Distributions with Natural Gradient Surrogates AISTATS 2024 Sobolev Space Regularised Pre Density Models ICML 2024 TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision ICML 2024 Understanding Stochastic Natural Gradient Variational Inference ICML 2024 Variational Gaussian Process Diffusion Processes AISTATS 2024 Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting ACML 2023 Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees JMLR 2023 Fisher-Legendre (FishLeg) optimization of deep neural networks ICLR 2023 Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation NeurIPS 2023 QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning NeurIPS 2023 The Bayesian Learning Rule JMLR 2023 Unbiased learning of deep generative models with structured discrete representations NeurIPS 2023