Monte Carlo Gradient Estimation in Machine Learning

25 June 2019

Papers citing "Monte Carlo Gradient Estimation in Machine Learning"

50 / 88 papers shown

Title
Secrets of GFlowNets' Learning Behavior: A Theoretical Study Tianshu Yu 26 0 0 04 May 2025
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards Zijing Hu Fengda Zhang Long Chen Kun Kuang Jiahui Li Kaifeng Gao Jun Xiao X. Wang Wenwu Zhu EGVM 56 0 0 14 Mar 2025
A Simple and Effective Reinforcement Learning Method for Text-to-Image Diffusion Fine-tuning Shashank Gupta Chaitanya Ahuja Tsung-Yu Lin Sreya Dutta Roy Harrie Oosterhuis Maarten de Rijke Satya Narayan Shukla 46 1 0 02 Mar 2025
Preference learning made easy: Everything should be understood through win rate Lily H. Zhang Rajesh Ranganath 85 0 0 14 Feb 2025
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior Tongda Xu Xiyan Cai X. Zhang Xingtong Ge Dailan He Ming Sun Jingjing Liu Y. Zhang Jian Li Yan Wang DiffM 120 1 0 31 Jan 2025
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 45 0 0 28 Jan 2025
Revisiting Ensemble Methods for Stock Trading and Crypto Trading Tasks at ACM ICAIF FinRL Contest 2023-2024 Nikolaus Holzer Keyi Wang Kairong Xiao Xiao-Yang Liu Yanglet AIFin 30 1 0 18 Jan 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference Jiayi Huang Sangwoo Park Osvaldo Simeone 105 2 0 03 Jan 2025
L3Ms -- Lagrange Large Language Models Guneet S. Dhillon Xingjian Shi Yee Whye Teh Alex Smola 145 0 0 28 Oct 2024
An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control Mengjian Hua Matthieu Laurière Eric Vanden-Eijnden 31 3 0 07 Oct 2024
Stabilizing the Kumaraswamy Distribution Max Wasserman Gonzalo Mateos BDL 44 0 0 01 Oct 2024
On the limits of agency in agent-based models Ayush Chopra Shashank Kumar Nurullah Giray-Kuru Ramesh Raskar Arnau Quera-Bofarull LLMAG AI4CE 42 7 0 14 Sep 2024
Alignment of Diffusion Models: Fundamentals, Challenges, and Future Buhua Liu Shitong Shao Bao Li Lichen Bai Zhiqiang Xu Haoyi Xiong James Kwok Sumi Helal Zeke Xie 42 12 0 11 Sep 2024
Variational Search Distributions Daniel M. Steinberg Rafael Oliveira Cheng Soon Ong Edwin V. Bonilla 33 0 0 10 Sep 2024
Particle Semi-Implicit Variational Inference Jen Ning Lim A. M. Johansen 43 3 0 30 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 53 0 0 03 Jun 2024
Learning Latent Graph Structures and their Uncertainty A. Manenti Daniele Zambon Cesare Alippi BDL 38 1 0 30 May 2024
cryoSPHERE: Single-particle heterogeneous reconstruction from cryo EM Gabriel Ducrocq Lukas Grunewald S. Westenhoff Fredrik Lindsten 25 1 0 29 May 2024
Deep generative modelling of canonical ensemble with differentiable thermal properties Shuo-Hui Li Yao-Wen Zhang Ding Pan DRL SyDa 36 1 0 29 Apr 2024
Efficient Combinatorial Optimization via Heat Diffusion He Ma Wenlian Lu Jianfeng Feng 31 1 0 13 Mar 2024
Explaining Probabilistic Models with Distributional Values Luca Franceschi Michele Donini Cédric Archambeau Matthias Seeger FAtt 37 2 0 15 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 30 2 0 19 Jan 2024
Score-Aware Policy-Gradient Methods and Performance Guarantees using Local Lyapunov Conditions: Applications to Product-Form Stochastic Networks and Queueing Systems Céline Comte Matthieu Jonckheere J. Sanders Albert Senen-Cerda 25 0 0 05 Dec 2023
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 21 1 0 26 Sep 2023
Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics Michael Kagan Lukas Heinrich 26 9 0 31 Aug 2023
Amortised Experimental Design and Parameter Estimation for User Models of Pointing Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 20 7 0 19 Jul 2023
Empirical Sample Complexity of Neural Network Mixed State Reconstruction Haimeng Zhao Giuseppe Carleo F. Vicentini 18 11 0 04 Jul 2023
Bayesian calibration of differentiable agent-based models Arnau Quera-Bofarull Ayush Chopra Anisoara Calinescu Michael Wooldridge Joel Dyer 26 9 0 24 May 2023
Efficient Halftoning via Deep Reinforcement Learning Haitian Jiang Dongliang Xiong Xiaowen Jiang Li Ding Liang Chen Kai Huang 13 3 0 24 Apr 2023
Learning Temporal Distribution and Spatial Correlation Towards Universal Moving Object Segmentation Guanfang Dong Chenqiu Zhao Xichen Pan Anup Basu VOS 26 3 0 19 Apr 2023
Differentiable Rendering with Reparameterized Volume Sampling Nikita Morozov D. Rakitin Oleg Desheulin Dmitry Vetrov Kirill Struminsky 19 4 0 21 Feb 2023
Directed Acyclic Graphs With Tears Zhichao Chen Zhiqiang Ge CML 33 5 0 04 Feb 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 27 11 0 27 Jan 2023
Graph state-space models Daniele Zambon Andrea Cini L. Livi Cesare Alippi 23 6 0 04 Jan 2023
RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT Alberto Huertas Celdrán Pedro Miguel Sánchez Sánchez Jan von der Assen T. Schenk Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller AAML 27 6 0 30 Dec 2022
Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value Function Clément Bonnet Laurence Midgley Alexandre Laterre 24 1 0 19 Nov 2022
Manifold Gaussian Variational Bayes on the Precision Matrix M. Magris M. Shabani Alexandros Iosifidis 37 2 0 26 Oct 2022
Arc travel time and path choice model estimation subsumed Sobhan Mohammadpour Emma Frejinger 14 1 0 25 Oct 2022
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya Moritz Schauer Frank Schafer Chris Rackauckas 23 34 0 16 Oct 2022
Bit Allocation using Optimization Tongda Xu Han-yi Gao Chenjian Gao Yuanyuan Wang Dailan He ... Mao Ye Hongwei Qin Yan Wang Jingjing Liu Ya-Qin Zhang 56 14 0 20 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 32 9 0 13 Sep 2022
Survival Mixture Density Networks Xintian Han Mark Goldstein Rajesh Ranganath 28 5 0 23 Aug 2022
A Survey on Model-based Reinforcement Learning Fan Luo Tian Xu Hang Lai Xiong-Hui Chen Weinan Zhang Yang Yu OffRL LRM 44 101 0 19 Jun 2022
A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks Z. Yang Richard Sinnott James Bailey Qiuhong Ke 23 39 0 14 Jun 2022
Sparse Graph Learning from Spatiotemporal Time Series Andrea Cini Daniele Zambon Cesare Alippi CML AI4TS 37 18 0 26 May 2022
Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality Selection Mingyu Yang Yu Chen Hun-Seok Kim 33 27 0 12 May 2022
An Introduction to Quantum Machine Learning for Engineers Osvaldo Simeone 11 46 0 11 May 2022
A Brief Overview of Unsupervised Neural Speech Representation Learning Lasse Borgholt Jakob Drachmann Havtorn Joakim Edin Lars Maaløe Christian Igel BDL AI4TS SSL 19 11 0 01 Mar 2022
Gradients without Backpropagation A. G. Baydin Barak A. Pearlmutter Don Syme Frank D. Wood Philip H. S. Torr 30 66 0 17 Feb 2022
A Differential Entropy Estimator for Training Neural Networks Georg Pichler Pierre Colombo Malik Boudiaf Günther Koliander Pablo Piantanida 25 21 0 14 Feb 2022