ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2002.04632
  4. Cited By
Black-Box Optimization with Local Generative Surrogates

Black-Box Optimization with Local Generative Surrogates

11 February 2020
S. Shirobokov
V. Belavin
Michael Kagan
Andrey Ustyuzhanin
A. G. Baydin
ArXivPDFHTML

Papers citing "Black-Box Optimization with Local Generative Surrogates"

10 / 10 papers shown
Title
The frontier of simulation-based inference
The frontier of simulation-based inference
Kyle Cranmer
Johann Brehmer
Gilles Louppe
AI4CE
80
834
0
04 Nov 2019
Automatic Posterior Transformation for Likelihood-Free Inference
Automatic Posterior Transformation for Likelihood-Free Inference
David S. Greenberg
M. Nonnenmacher
Jakob H. Macke
106
319
0
17 May 2019
Conditioning by adaptive sampling for robust design
Conditioning by adaptive sampling for robust design
David H. Brookes
Hahnbeom Park
Jennifer Listgarten
41
197
0
29 Jan 2019
Pyro: Deep Universal Probabilistic Programming
Pyro: Deep Universal Probabilistic Programming
Eli Bingham
Jonathan P. Chen
M. Jankowiak
F. Obermeyer
Neeraj Pradhan
Theofanis Karaletsos
Rohit Singh
Paul A. Szerlip
Paul Horsfall
Noah D. Goodman
BDL
GP
83
1,043
0
18 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative
  Models
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl
Ricky T. Q. Chen
J. Bettencourt
Ilya Sutskever
David Duvenaud
DRL
40
861
0
02 Oct 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with
  Autoregressive Flows
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows
George Papamakarios
D. Sterratt
Iain Murray
BDL
180
360
0
18 May 2018
Improving Generalization Performance by Switching from Adam to SGD
Improving Generalization Performance by Switching from Adam to SGD
N. Keskar
R. Socher
ODL
57
522
0
20 Dec 2017
Don't Decay the Learning Rate, Increase the Batch Size
Don't Decay the Learning Rate, Increase the Batch Size
Samuel L. Smith
Pieter-Jan Kindermans
Chris Ying
Quoc V. Le
ODL
73
990
0
01 Nov 2017
A Compositional Object-Based Approach to Learning Physical Dynamics
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
T. Ullman
Antonio Torralba
J. Tenenbaum
AI4CE
OCL
300
439
0
01 Dec 2016
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
106
2,911
0
07 Oct 2016
1