Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1612.01936
Cited By
A Probabilistic Framework for Deep Learning
6 December 2016
Ankit B. Patel
M. T. Nguyen
Richard G. Baraniuk
BDL
Re-assign community
ArXiv
PDF
HTML
Papers citing
"A Probabilistic Framework for Deep Learning"
31 / 31 papers shown
Title
Be Bayesian by Attachments to Catch More Uncertainty
Shiyu Shen
Bin Pan
Tianyang Shi
Tao Li
Zhenwei Shi
UQCV
35
0
0
19 Oct 2023
Improving Transformers with Probabilistic Attention Keys
Tam Nguyen
T. Nguyen
Dung D. Le
Duy Khuong Nguyen
Viet-Anh Tran
Richard G. Baraniuk
Nhat Ho
Stanley J. Osher
53
32
0
16 Oct 2021
A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability
Xinjie Lan
Kenneth Barner
FAtt
14
2
0
27 Oct 2020
Multi-layer Residual Sparsifying Transform (MARS) Model for Low-dose CT Image Reconstruction
Xikai Yang
Y. Long
S. Ravishankar
MedIm
32
3
0
10 Oct 2020
The Gaussian equivalence of generative models for learning with shallow neural networks
Sebastian Goldt
Bruno Loureiro
Galen Reeves
Florent Krzakala
M. Mézard
Lenka Zdeborová
BDL
41
100
0
25 Jun 2020
Explicitly Bayesian Regularizations in Deep Learning
Xinjie Lan
Kenneth Barner
UQCV
BDL
AI4CE
14
1
0
22 Oct 2019
Modelling the influence of data structure on learning in neural networks: the hidden manifold model
Sebastian Goldt
M. Mézard
Florent Krzakala
Lenka Zdeborová
BDL
29
51
0
25 Sep 2019
A Probabilistic Representation of Deep Learning
Xinjie Lan
Kenneth Barner
UQCV
BDL
AI4CE
14
1
0
26 Aug 2019
Kernel Mode Decomposition and programmable/interpretable regression networks
H. Owhadi
C. Scovel
G. Yoo
16
5
0
19 Jul 2019
A synthetic dataset for deep learning
Xinjie Lan
9
3
0
01 Jun 2019
Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks
Shuai Li
15
2
0
30 Nov 2018
A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model
Yujia Wang
Nhat Ho
David J. Miller
Anima Anandkumar
Michael I. Jordan
Richard G. Baraniuk
BDL
GAN
29
8
0
01 Nov 2018
Rediscovering Deep Neural Networks Through Finite-State Distributions
Amir Emad Marvasti
Ehsan Emad Marvasti
George Atia
H. Foroosh
17
0
0
26 Sep 2018
Sleep-wake classification via quantifying heart rate variability by convolutional neural network
John Malik
Y. Lo
Hau‐Tieng Wu
11
53
0
01 Aug 2018
On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks
Jeremias Sulam
Aviad Aberdam
Amir Beck
Michael Elad
19
92
0
02 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test?
Adam S. Charles
AAML
HAI
AI4CE
24
9
0
01 Jun 2018
Mad Max: Affine Spline Insights into Deep Learning
Randall Balestriero
Richard Baraniuk
AI4CE
31
78
0
17 May 2018
A Provably Correct Algorithm for Deep Learning that Actually Works
Eran Malach
Shai Shalev-Shwartz
MLT
8
30
0
26 Mar 2018
Deep Component Analysis via Alternating Direction Neural Networks
Calvin Murdock
Ming-Fang Chang
Simon Lucey
BDL
27
20
0
16 Mar 2018
Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion
Randall Balestriero
H. Glotin
Richard Baraniuk
BDL
24
5
0
27 Feb 2018
Semi-Supervised Learning via New Deep Network Inversion
Randall Balestriero
Vincent Roger
H. Glotin
Richard G. Baraniuk
19
3
0
12 Nov 2017
Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning
Jeremias Sulam
Vardan Papyan
Yaniv Romano
Michael Elad
29
111
0
29 Aug 2017
Learning like humans with Deep Symbolic Networks
Qunzhi Zhang
D. Sornette
13
9
0
11 Jul 2017
Inference in Deep Networks in High Dimensions
A. Fletcher
S. Rangan
BDL
11
68
0
20 Jun 2017
von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification
Abul Hasnat
Julien Bohné
Jonathan Milgram
S. Gentric
Liming Chen
CVBM
42
91
0
13 Jun 2017
Blind nonnegative source separation using biological neural networks
Cengiz Pehlevan
S. Mohan
D. Chklovskii
18
38
0
01 Jun 2017
Learning to Invert: Signal Recovery via Deep Convolutional Networks
Ali Mousavi
Richard G. Baraniuk
21
285
0
14 Jan 2017
Deep Learning and Hierarchal Generative Models
Elchanan Mossel
BDL
GAN
20
23
0
29 Dec 2016
Semi-Supervised Learning with the Deep Rendering Mixture Model
M. T. Nguyen
Wanjia Liu
Ethan Perez
Richard G. Baraniuk
Ankit B. Patel
BDL
16
9
0
06 Dec 2016
Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation
D. L. Richmond
Dagmar Kainmüller
M. Yang
E. Myers
Carsten Rother
SSeg
15
14
0
27 Jul 2015
Qualitative Robustness in Bayesian Inference
H. Owhadi
C. Scovel
48
26
0
14 Nov 2014
1