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Stochastic Processes

2667 directly classified papers

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Papers

Negative-Binomial Randomized Gamma Dynamical Systems for Heterogeneous Overdispersed Count Time Sequences IJCAI 2024
TaD: A Plug-and-Play Task-Aware Decoding Method to Better Adapt LLMs on Downstream Tasks IJCAI 2024
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint AISTATS 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications AISTATS 2024
Random Oscillators Network for Time Series Processing AISTATS 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024
A Greedy Approximation for k-Determinantal Point Processes AISTATS 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024
Temporal Graph ODEs for Irregularly-Sampled Time Series IJCAI 2024
Can't Be Late: Optimizing Spot Instance Savings under Deadlines NSDI 2024
DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering NIPS 2024
Nonstationary Sparse Spectral Permanental Process NIPS 2024
Grokking phase transitions in learning local rules with gradient descent JMLR 2024
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NIPS 2024
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness NIPS 2024
Tensor-train methods for sequential state and parameter learning in state-space models JMLR 2024
A scalable generative model for dynamical system reconstruction from neuroimaging data NIPS 2024
Structural Inference of Dynamical Systems with Conjoined State Space Models NIPS 2024
A Comparison of Continuous-Time Approximations to Stochastic Gradient Descent JMLR 2024
Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model NIPS 2024
Minimum Entropy Coupling with Bottleneck NIPS 2024
Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics IJCAI 2024
Learning World Models for Unconstrained Goal Navigation NIPS 2024
Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics NIPS 2024