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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at
  Scale

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

8 July 2019
A. G. Baydin
Lei Shao
W. Bhimji
Lukas Heinrich
Lawrence Meadows
Jialin Liu
Andreas Munk
Saeid Naderiparizi
Bradley Gram-Hansen
Gilles Louppe
Mingfei Ma
Xiaohui Zhao
Philip H. S. Torr
Victor W. Lee
Kyle Cranmer
P. Prabhat
Frank D. Wood
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Papers citing "Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale"

14 / 14 papers shown
Title
Neural Amortized Inference for Nested Multi-agent Reasoning
Neural Amortized Inference for Nested Multi-agent Reasoning
Kunal Jha
T. Le
Chuanyang Jin
Yen-Ling Kuo
J. Tenenbaum
Tianmin Shu
LLMAG
AI4CE
15
5
0
21 Aug 2023
Efficient Data Mosaicing with Simulation-based Inference
Efficient Data Mosaicing with Simulation-based Inference
Andrew Gambardella
Youngjun Choi
Doyo Choi
Jinjoon Lee
21
0
0
26 Oct 2022
A Probabilistic Machine Learning Approach to Scheduling Parallel Loops
  with Bayesian Optimization
A Probabilistic Machine Learning Approach to Scheduling Parallel Loops with Bayesian Optimization
Kyurae Kim
Youngjae Kim
Sungyong Park
21
12
0
12 Jun 2022
Guaranteed Bounds for Posterior Inference in Universal Probabilistic
  Programming
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming
Raven Beutner
Luke Ong
Fabian Zaiser
14
11
0
06 Apr 2022
Compartmental Models for COVID-19 and Control via Policy Interventions
Compartmental Models for COVID-19 and Control via Policy Interventions
Swapneel Mehta
Noah Kasmanoff
11
0
0
06 Mar 2022
Group equivariant neural posterior estimation
Group equivariant neural posterior estimation
Maximilian Dax
Stephen R. Green
J. Gair
Michael Deistler
Bernhard Schölkopf
Jakob H. Macke
BDL
33
31
0
25 Nov 2021
Detecting and Quantifying Malicious Activity with Simulation-based
  Inference
Detecting and Quantifying Malicious Activity with Simulation-based Inference
Andrew Gambardella
Bogdan State
Naemullah Khan
Leo Tsourides
Philip H. S. Torr
A. G. Baydin
20
2
0
06 Oct 2021
Benchmarking Simulation-Based Inference
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann
Jan Boelts
David S. Greenberg
P. J. Gonçalves
Jakob H. Macke
104
184
0
12 Jan 2021
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning
  Study
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study
Himanshu Sharma
Elise Jennings
BDL
21
3
0
23 May 2020
Efficient Probabilistic Inference in the Quest for Physics Beyond the
  Standard Model
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
A. G. Baydin
Lukas Heinrich
W. Bhimji
Lei Shao
Saeid Naderiparizi
...
Philip Torr
Victor W. Lee
P. Prabhat
Kyle Cranmer
Frank D. Wood
15
31
0
20 Jul 2018
Fast inference of deep neural networks in FPGAs for particle physics
Fast inference of deep neural networks in FPGAs for particle physics
Javier Mauricio Duarte
Song Han
Philip C. Harris
S. Jindariani
E. Kreinar
...
J. Ngadiuba
M. Pierini
R. Rivera
N. Tran
Zhenbin Wu
AI4CE
75
386
0
16 Apr 2018
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,743
0
26 Sep 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,888
0
15 Sep 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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