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. 1802.04537
  4. Cited By
Tighter Variational Bounds are Not Necessarily Better

Tighter Variational Bounds are Not Necessarily Better

13 February 2018
Tom Rainforth
Adam R. Kosiorek
T. Le
Chris J. Maddison
Maximilian Igl
Frank Wood
Yee Whye Teh
    DRL
ArXivPDFHTML

Papers citing "Tighter Variational Bounds are Not Necessarily Better"

5 / 55 papers shown
Title
Scalable Bayesian Learning for State Space Models using Variational
  Inference with SMC Samplers
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers
Marcel Hirt
P. Dellaportas
BDL
20
10
0
23 May 2018
Semi-Amortized Variational Autoencoders
Semi-Amortized Variational Autoencoders
Yoon Kim
Sam Wiseman
Andrew C. Miller
David Sontag
Alexander M. Rush
BDL
DRL
33
243
0
07 Feb 2018
Faithful Inversion of Generative Models for Effective Amortized
  Inference
Faithful Inversion of Generative Models for Effective Amortized Inference
Stefan Webb
Adam Goliñski
R. Zinkov
Siddharth Narayanaswamy
Tom Rainforth
Yee Whye Teh
Frank Wood
TPM
51
46
0
01 Dec 2017
Advances in Variational Inference
Advances in Variational Inference
Cheng Zhang
Judith Butepage
Hedvig Kjellström
Stephan Mandt
BDL
38
684
0
15 Nov 2017
Auto-Encoding Sequential Monte Carlo
Auto-Encoding Sequential Monte Carlo
T. Le
Maximilian Igl
Tom Rainforth
Tom Jin
Frank Wood
BDL
DRL
26
151
0
29 May 2017
Previous
12