A Probabilistic Framework for Deep Learning

6 December 2016

Richard G. Baraniuk

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 11 3 0 01 Jun 2019
Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks Shuai Li 17 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 22 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 10 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 27 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 15 9 0 11 Jul 2017
Inference in Deep Networks in High Dimensions A. Fletcher S. Rangan BDL 13 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 23 285 0 14 Jan 2017
Deep Learning and Hierarchal Generative Models Elchanan Mossel BDL GAN 22 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 18 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