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Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical
  Guarantees and Implementation Details

Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details

25 August 2021
Sanket R. Jantre
Shrijita Bhattacharya
T. Maiti
    BDL
ArXivPDFHTML

Papers citing "Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details"

10 / 10 papers shown
Title
Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis
Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis
Sanket R. Jantre
Tianle Wang
Gilchan Park
Kriti Chopra
Nicholas Jeon
Xiaoning Qian
Nathan M. Urban
Byung-Jun Yoon
62
0
0
10 Feb 2025
BMRS: Bayesian Model Reduction for Structured Pruning
BMRS: Bayesian Model Reduction for Structured Pruning
Dustin Wright
Christian Igel
Raghavendra Selvan
BDL
MQ
44
0
0
03 Jun 2024
Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning
  of Variational Autoencoders
Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders
Nafiz Abeer
Sanket R. Jantre
Nathan M. Urban
Byung-Jun Yoon
45
0
0
31 May 2024
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in
  Deep Generative Models for Molecular Design
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design
A. N. M. N. Abeer
Sanket R. Jantre
Nathan M. Urban
Byung-Jun Yoon
55
1
0
30 Apr 2024
Bayesian sparsification for deep neural networks with Bayesian model
  reduction
Bayesian sparsification for deep neural networks with Bayesian model reduction
Dimitrije Marković
K. Friston
S. Kiebel
BDL
UQCV
38
1
0
21 Sep 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its
  Posterior Inference
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong
Dongyoon Yang
Jongjin Lee
Ilsang Ohn
Gyuseung Baek
Yongdai Kim
BDL
34
4
0
24 May 2023
Projective Integral Updates for High-Dimensional Variational Inference
Projective Integral Updates for High-Dimensional Variational Inference
J. Duersch
35
1
0
20 Jan 2023
Unified Probabilistic Neural Architecture and Weight Ensembling Improves
  Model Robustness
Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness
Sumegha Premchandar
Sandeep Madireddy
Sanket R. Jantre
Prasanna Balaprakash
OOD
UQCV
13
3
0
08 Oct 2022
Deep neural networks with dependent weights: Gaussian Process mixture
  limit, heavy tails, sparsity and compressibility
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility
Hoileong Lee
Fadhel Ayed
Paul Jung
Juho Lee
Hongseok Yang
François Caron
46
10
0
17 May 2022
Consistent Sparse Deep Learning: Theory and Computation
Consistent Sparse Deep Learning: Theory and Computation
Y. Sun
Qifan Song
F. Liang
BDL
43
27
0
25 Feb 2021
1