Research Explorer
Papers
Conferences
Authors
Topics
Keywords
Trends
Achievements
Explore
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Stochastic Processes
2667 directly classified papers
Papers per year
2003: 4
2004: 1
2005: 2
2006: 9
2007: 11
2008: 17
2009: 18
2010: 30
2011: 36
2012: 37
2013: 50
2014: 56
2015: 60
2016: 77
2017: 132
2018: 154
2019: 211
2020: 244
2021: 311
2022: 279
2023: 376
2024: 326
2025: 157
2026: 69
Papers
SynWeather: Weather Observation Data Synthesis Across Multiple Regions and Variables via a General Diffusion Transformer
AAAI 2026
Breaking One-Size-Fits-All: Revisiting Out-of-Distribution Detection on Graphs Under Diverse Distribution Shifts
AAAI 2026
Detection of Adversarial Prompts with Model Predictive Entropy
EACL 2026
Modeling Trend Dynamics with Variational Neural ODEs for Information Popularity Prediction
AAAI 2026
Gaussian Uncertainty-Driven Multi-Model Fitting with Graph Neural Network
AAAI 2026
METP: Multi-Granularity Integration of External Covariates for Temporal Point Processes
AAAI 2026
Scalpel: Fine-Grained Alignment of Attention Activation Manifolds via Mixture Gaussian Bridges to Mitigate Multimodal Hallucination
WACV 2026
Chronocept: Instilling a Sense of Time in Machines
EACL 2026
Energy-based Autoregressive Generation for Neural Population Dynamics
AAAI 2026
EPO: Diverse and Realistic Protein Ensemble Generation via Energy Preference Optimization
AAAI 2026
Spatio-Temporal Context Learning with Temporal Difference Convolution for Moving Infrared Small Target Detection
AAAI 2026
Pre-Trained Video Generative Models as World Simulators
AAAI 2026
Relative Advantage Debiasing for Watch-Time Prediction in Short-Video Recommendation
AAAI 2026
Simulation-Driven Railway Delay Prediction: An Imitation Learning Approach
AAAI 2026
Modeling and Learning Multiple Hypotheses for Monocular 3D Object Detection
WACV 2026
Joint Modeling of Corruption-Driven and Information-Limited Uncertainty for Robust 3D Gaussian Splatting
WACV 2026
Martingale Foresight Sampling: A Principled Approach to Inference-Time LLM Decoding
EACL 2026
Statistical Foundations of DIME: Risk Estimation for Practical Index Selection
EACL 2026
BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow Generation
EACL 2026
ProAR: Probabilistic Autoregressive Modeling for Molecular Dynamics
AAAI 2026
WeightFlow: Learning Stochastic Dynamics via Evolving Weight of Neural Network
AAAI 2026
Structure-based RNA Design by Step-wise Optimization of Latent Diffusion Model
AAAI 2026
Tree-Based Stochastic Optimization for Solving Large-Scale Urban Network Security Games
AAAI 2026
SyncBrain: Exploring Brain Functional Dynamics Through Neural Oscillatory Synchronization
AAAI 2026
Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation
AAAI 2026
<
1
2
3
4
5
…
107
>