Adversarial Variational Optimization of Non-Differentiable Simulators

22 July 2017

Papers citing "Adversarial Variational Optimization of Non-Differentiable Simulators"

20 / 20 papers shown

Title
Predictive variational inference: Learn the predictively optimal posterior distribution Jinlin Lai Yuling Yao BDL 31 0 0 18 Oct 2024
End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver Shaocong Ma James Diffenderfer B. Kailkhura Yi Zhou AI4CE 40 0 0 17 Apr 2024
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing Nataniel Ruiz Sarah Adel Bargal Cihang Xie Kate Saenko Stan Sclaroff ViT 33 5 0 29 Nov 2022
Human Body Measurement Estimation with Adversarial Augmentation Nataniel Ruiz Míriam Bellver Timo Bolkart Ambuj Arora Ming-Chia Lin Javier Romero Raj Bala 3DH 37 3 0 11 Oct 2022
Compositional Score Modeling for Simulation-based Inference Tomas Geffner George Papamakarios A. Mnih 69 24 0 28 Sep 2022
Neural-Sim: Learning to Generate Training Data with NeRF Yunhao Ge Harkirat Singh Behl Jiashu Xu Suriya Gunasekar Neel Joshi Ya-heng Song Xin Eric Wang Laurent Itti Vibhav Vineet 29 33 0 22 Jul 2022
Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection Takahiro Suzuki S. Hanaoka Issei Sato OOD MedIm 26 1 0 29 Apr 2022
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data Samarth Mishra Rameswar Panda Cheng Perng Phoo Chun-Fu Chen Leonid Karlinsky Kate Saenko Venkatesh Saligrama Rogerio Feris 26 33 0 30 Nov 2021
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search Kartik Hegde Po-An Tsai Sitao Huang Vikas Chandra A. Parashar Christopher W. Fletcher 26 90 0 02 Mar 2021
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 16 27 0 11 Nov 2020
Generalised Bayes Updates with $f$ -divergences through Probabilistic Classifiers Owen Thomas Henri Pesonen J. Corander FedML 26 2 0 08 Jul 2020
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 23 14 0 04 Jun 2019
Meta-Sim: Learning to Generate Synthetic Datasets Amlan Kar Aayush Prakash Ming-Yu Liu Eric Cameracci Justin Yuan Matt Rusiniak David Acuna Antonio Torralba Sanja Fidler 11 247 0 25 Apr 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 29 20 0 10 Mar 2019
Learning To Simulate Nataniel Ruiz S. Schulter Manmohan Chandraker 27 119 0 05 Oct 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 38 180 0 30 May 2018
Synthesizing Programs for Images using Reinforced Adversarial Learning Yaroslav Ganin Tejas D. Kulkarni Igor Babuschkin A. Eslami Oriol Vinyals GAN 12 229 0 03 Apr 2018
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization Adam McCarthy Blanca Rodriguez A. Mincholé 36 5 0 09 Dec 2017
Variational Optimization J. Staines David Barber DRL 65 53 0 18 Dec 2012