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Stochastic Processes

2,667 papers

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Papers

Stochastic Optimal Control for Diffusion Bridges in Function Spaces NIPS 2024
Global Convergence in Training Large-Scale Transformers NIPS 2024
Constrained Sampling with Primal-Dual Langevin Monte Carlo NIPS 2024
Kermut: Composite kernel regression for protein variant effects NIPS 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NIPS 2024
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals NIPS 2024
Neural Persistence Dynamics NIPS 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NIPS 2024
Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach NIPS 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory NIPS 2024
Certified Machine Unlearning via Noisy Stochastic Gradient Descent NIPS 2024
Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks NIPS 2024
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input NIPS 2024
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos NIPS 2024
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction NIPS 2024
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning NIPS 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons NIPS 2024
Graph Neural Networks Do Not Always Oversmooth NIPS 2024
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression NIPS 2024
Gradients of Functions of Large Matrices NIPS 2024
Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport NIPS 2024
Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model NIPS 2024
Learning World Models for Unconstrained Goal Navigation NIPS 2024
Minimum Entropy Coupling with Bottleneck NIPS 2024
SGD vs GD: Rank Deficiency in Linear Networks NIPS 2024