{"total":25,"rows":[{"id":"2302.00111","title":"Learning Universal Policies via Text-Guided Video Generation","created":"2023-01-31","cited_by_count":522,"area":null},{"id":"2101.03288","title":"How to Train Your Energy-Based Models","created":"2021-01-09","cited_by_count":274,"area":null},{"id":"2202.01361","title":"Generative Flow Networks for Discrete Probabilistic Modeling","created":"2022-02-03","cited_by_count":114,"area":null},{"id":"2111.09297","title":"Learning to Compose Visual Relations","created":"2021-11-17","cited_by_count":72,"area":null},{"id":"2207.07150","title":"Making Linear MDPs Practical via Contrastive Representation Learning","created":"2022-07-14","cited_by_count":52,"area":null},{"id":"2108.09093","title":"Towards Understanding the Generative Capability of Adversarially Robust Classifiers","created":"2021-08-20","cited_by_count":26,"area":null},{"id":"2206.14897","title":"Discrete Langevin Sampler via Wasserstein Gradient Flow","created":"2022-06-29","cited_by_count":24,"area":null},{"id":"2212.08791","title":"Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective","created":"2022-12-17","cited_by_count":13,"area":null},{"id":"2204.12301","title":"Designing Perceptual Puzzles by Differentiating Probabilistic Programs","created":"2022-04-26","cited_by_count":12,"area":null},{"id":"2110.15397","title":"A Computationally Efficient Method for Learning Exponential Family Distributions","created":"2021-10-28","cited_by_count":10,"area":null},{"id":"2107.05134","title":"Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks","created":"2021-07-11","cited_by_count":8,"area":null},{"id":"2303.16189","title":"Planning with Sequence Models through Iterative Energy Minimization","created":"2023-03-28","cited_by_count":8,"area":null},{"id":"2111.00780","title":"Pseudo-Spherical Contrastive Divergence","created":"2021-11-01","cited_by_count":7,"area":null},{"id":"2112.14195","title":"Exponential Family Model-Based Reinforcement Learning via Score Matching","created":"2021-12-28","cited_by_count":5,"area":null},{"id":"2304.10707","title":"Persistently Trained, Diffusion-assisted Energy-based Models","created":"2023-04-21","cited_by_count":4,"area":null},{"id":"2306.00684","title":"Balanced Training of Energy-Based Models with Adaptive Flow Sampling","created":"2023-06-01","cited_by_count":4,"area":null},{"id":"2209.15092","title":"Improving Generative Flow Networks with Path Regularization","created":"2022-09-29","cited_by_count":3,"area":null},{"id":"2202.06460","title":"Simultaneous Transport Evolution for Minimax Equilibria on Measures","created":"2022-02-14","cited_by_count":2,"area":null},{"id":"2309.06413","title":"On Computationally Efficient Learning of Exponential Family Distributions","created":"2023-09-12","cited_by_count":2,"area":null},{"id":"2312.12849","title":"Divergences induced by dual subtractive and divisive normalizations of exponential families and their convex deformations","created":"2023-12-20","cited_by_count":2,"area":null},{"id":"2505.18983","title":"AmorLIP: Efficient Language-Image Pretraining via Amortization","created":"2025-05-25","cited_by_count":2,"area":null},{"id":"2111.01035","title":"A Unified View of cGANs with and without Classifiers","created":"2021-11-01","cited_by_count":1,"area":null},{"id":"2410.20760","title":"Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances","created":"2024-10-28","cited_by_count":1,"area":null},{"id":"2105.04769","title":"Scalable Personalised Item Ranking through Parametric Density Estimation","created":"2021-05-11","cited_by_count":0,"area":null},{"id":"2601.20154","title":"Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning","created":"2026-01-28","cited_by_count":0,"area":null}],"next_cursor":null}