{"total":24,"rows":[{"id":"2106.01798","title":"Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions","created":"2021-06-03","cited_by_count":98,"area":null},{"id":"2110.01515","title":"A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning","created":"2021-10-04","cited_by_count":82,"area":null},{"id":"2202.09497","title":"Gradient Estimation with Discrete Stein Operators","created":"2022-02-19","cited_by_count":23,"area":null},{"id":"2205.13492","title":"Sparse Graph Learning from Spatiotemporal Time Series","created":"2022-05-26","cited_by_count":22,"area":null},{"id":"2311.12569","title":"Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick","created":"2023-11-21","cited_by_count":14,"area":null},{"id":"2209.04862","title":"Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models","created":"2022-09-11","cited_by_count":12,"area":null},{"id":"2104.00428","title":"Storchastic: A Framework for General Stochastic Automatic Differentiation","created":"2021-04-01","cited_by_count":11,"area":null},{"id":"2109.11034","title":"Conditional Poisson Stochastic Beam Search","created":"2021-09-22","cited_by_count":11,"area":null},{"id":"2106.08056","title":"Coupled Gradient Estimators for Discrete Latent Variables","created":"2021-06-15","cited_by_count":9,"area":null},{"id":"2203.01629","title":"Learning Group Importance using the Differentiable Hypergeometric Distribution","created":"2022-03-03","cited_by_count":5,"area":null},{"id":"2206.00583","title":"Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks","created":"2022-06-01","cited_by_count":5,"area":null},{"id":"2110.14002","title":"CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator","created":"2021-10-26","cited_by_count":4,"area":null},{"id":"2302.11793","title":"Revisiting the Gumbel-Softmax in MADDPG","created":"2023-02-23","cited_by_count":3,"area":null},{"id":"2112.03638","title":"Scaling Structured Inference with Randomization","created":"2021-12-07","cited_by_count":2,"area":null},{"id":"2205.01324","title":"Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies","created":"2022-05-03","cited_by_count":2,"area":null},{"id":"2205.12621","title":"Unbiased and Efficient Sampling of Dependency Trees","created":"2022-05-25","cited_by_count":2,"area":null},{"id":"2201.00695","title":"An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation","created":"2021-12-24","cited_by_count":1,"area":null},{"id":"2210.13011","title":"On Many-Actions Policy Gradient","created":"2022-10-24","cited_by_count":1,"area":null},{"id":"2506.07687","title":"Rao-Blackwellised Reparameterisation Gradients","created":"2025-06-09","cited_by_count":1,"area":null},{"id":"2309.03974","title":"DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation","created":"2023-09-07","cited_by_count":0,"area":null},{"id":"2509.24728","title":"Beyond Softmax: A Natural Parameterization for Categorical Random Variables","created":"2025-09-29","cited_by_count":0,"area":null},{"id":"2602.09038","title":"Scaling GraphLLM with Bilevel-Optimized Sparse Querying","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2606.26369","title":"Scoring Is Not Enough: Addressing Gaps in Utility-fairness Trade-offs for Ranking","created":"2026-06-24","cited_by_count":0,"area":null},{"id":"2607.11146","title":"Rank-Conditioned Sample Reuse for the Plackett--Luce Best-of-$K$ Objective","created":"2026-07-13","cited_by_count":0,"area":null}],"next_cursor":null}