On the ability of neural nets to express distributions

On the ability of neural nets to express distributions

22 February 2017

Andrej Risteski

Papers citing "On the ability of neural nets to express distributions"

12 / 12 papers shown

Title
Non-identifiability distinguishes Neural Networks among Parametric Models Sourav Chatterjee Timothy Sudijono 30 0 0 25 Apr 2025
Generative adversarial learning with optimal input dimension and its adaptive generator architecture Zhiyao Tan Ling Zhou Huazhen Lin GAN 42 0 0 06 May 2024
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective Tanya Marwah Zachary Chase Lipton Jianfeng Lu Andrej Risteski 52 10 0 21 Oct 2022
Transformers Learn Shortcuts to Automata Bingbin Liu Jordan T. Ash Surbhi Goel A. Krishnamurthy Cyril Zhang OffRL LRM 46 156 0 19 Oct 2022
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms Surbhi Goel Sham Kakade Adam Tauman Kalai Cyril Zhang 32 1 0 01 Sep 2022
Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky's Theorem Clayton Sanford Vaggos Chatziafratis 14 1 0 19 Oct 2021
High-Dimensional Distribution Generation Through Deep Neural Networks Dmytro Perekrestenko Léandre Eberhard Helmut Bölcskei OOD 30 6 0 26 Jul 2021
EnCoD: Distinguishing Compressed and Encrypted File Fragments Fabio De Gaspari Dorjan Hitaj Giulio Pagnotta Lorenzo De Carli L. Mancini 20 18 0 15 Oct 2020
The Barron Space and the Flow-induced Function Spaces for Neural Network Models E. Weinan Chao Ma Lei Wu 30 109 0 18 Jun 2019
Learning Neural Models for End-to-End Clustering B. Meier Ismail Elezi Mohammadreza Amirian Oliver Durr Thilo Stadelmann SSL 14 16 0 11 Jul 2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond Xingguo Li Junwei Lu Zhaoran Wang Jarvis Haupt T. Zhao 27 78 0 13 Jun 2018
Benefits of depth in neural networks Matus Telgarsky 148 602 0 14 Feb 2016