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. 1905.06922
  4. Cited By
On Variational Bounds of Mutual Information

On Variational Bounds of Mutual Information

16 May 2019
Ben Poole
Sherjil Ozair
Aaron van den Oord
Alexander A. Alemi
George Tucker
    SSL
ArXivPDFHTML

Papers citing "On Variational Bounds of Mutual Information"

21 / 21 papers shown
Title
InfoPO: On Mutual Information Maximization for Large Language Model Alignment
InfoPO: On Mutual Information Maximization for Large Language Model Alignment
Teng Xiao
Zhen Ge
Sujay Sanghavi
Tian Wang
Julian Katz-Samuels
Marc Versage
Qingjun Cui
Trishul Chilimbi
72
0
0
13 May 2025
MInCo: Mitigating Information Conflicts in Distracted Visual Model-based Reinforcement Learning
MInCo: Mitigating Information Conflicts in Distracted Visual Model-based Reinforcement Learning
Shiguang Sun
Hanbo Zhang
Zeyang Liu
Xinrui Yang
Lipeng Wan
Bing Yan
Xingyu Chen
Xuguang Lan
101
0
0
05 Apr 2025
The "Law" of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities
Yongwei Che
Benjamin Eysenbach
48
1
0
20 Jan 2025
Learning to Assist Humans without Inferring Rewards
Learning to Assist Humans without Inferring Rewards
Vivek Myers
Evan Ellis
Sergey Levine
Benjamin Eysenbach
Anca Dragan
79
3
0
17 Jan 2025
Interpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratios
Interpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratios
Marko Tuononen
Dani Korpi
Ville Hautamäki
FAtt
46
2
0
10 Jan 2025
Constructing Fair Latent Space for Intersection of Fairness and Explainability
Constructing Fair Latent Space for Intersection of Fairness and Explainability
Hyungjun Joo
Hyeonggeun Han
Sehwan Kim
Sangwoo Hong
Jungwoo Lee
54
0
0
23 Dec 2024
Surveying the space of descriptions of a composite system with machine learning
Surveying the space of descriptions of a composite system with machine learning
Kieran A. Murphy
Yujing Zhang
D. Bassett
97
0
0
27 Nov 2024
Bounds on Lp errors in density ratio estimation via f-divergence loss functions
Bounds on Lp errors in density ratio estimation via f-divergence loss functions
Yoshiaki Kitazawa
57
0
0
02 Oct 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
Wenyu Mao
Jiancan Wu
Haoyang Liu
Yongduo Sui
Xiang Wang
OOD
64
2
0
03 Aug 2024
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers
Chongyi Zheng
Anca Dragan
Sergey Levine
Benjamin Eysenbach
OffRL
68
9
0
24 Jun 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows
Variational Bayesian Optimal Experimental Design with Normalizing Flows
Jiayuan Dong
Christian L. Jacobsen
Mehdi Khalloufi
Maryam Akram
Wanjiao Liu
Karthik Duraisamy
Xun Huan
BDL
78
7
0
08 Apr 2024
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
Benjamin Eysenbach
Vivek Myers
Ruslan Salakhutdinov
Sergey Levine
AI4TS
72
8
0
06 Mar 2024
LIMIT: Learning Interfaces to Maximize Information Transfer
LIMIT: Learning Interfaces to Maximize Information Transfer
Benjamin A. Christie
Dylan P. Losey
41
4
0
17 Apr 2023
CoMIR: Contrastive Multimodal Image Representation for Registration
CoMIR: Contrastive Multimodal Image Representation for Registration
Nicolas Pielawski
Elisabeth Wetzer
Johan Öfverstedt
Jiahao Lu
Carolina Wählby
Joakim Lindblad
Natavsa Sladoje
40
81
0
11 Jun 2020
Towards a Definition of Disentangled Representations
Towards a Definition of Disentangled Representations
I. Higgins
David Amos
David Pfau
S. Racanière
Loic Matthey
Danilo Jimenez Rezende
Alexander Lerchner
OCL
DRL
57
475
0
05 Dec 2018
Formal Limitations on the Measurement of Mutual Information
Formal Limitations on the Measurement of Mutual Information
David A. McAllester
K. Stratos
SSL
44
275
0
10 Nov 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
35
1,336
0
16 Feb 2018
On Nesting Monte Carlo Estimators
On Nesting Monte Carlo Estimators
Tom Rainforth
R. Cornish
Hongseok Yang
Andrew Warrington
Frank Wood
87
131
0
18 Sep 2017
f-GAN: Training Generative Neural Samplers using Variational Divergence
  Minimization
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
GAN
55
1,648
0
02 Jun 2016
Deep Learning and the Information Bottleneck Principle
Deep Learning and the Information Bottleneck Principle
Naftali Tishby
Noga Zaslavsky
DRL
77
1,570
0
09 Mar 2015
A Fast and Simple Algorithm for Training Neural Probabilistic Language
  Models
A Fast and Simple Algorithm for Training Neural Probabilistic Language Models
A. Mnih
Yee Whye Teh
66
578
0
27 Jun 2012
1