Capacity and Trainability in Recurrent Neural Networks

29 November 2016

Papers citing "Capacity and Trainability in Recurrent Neural Networks"

21 / 21 papers shown

Title
The impact of allocation strategies in subset learning on the expressive power of neural networks Ofir Schlisselberg Ran Darshan 91 0 0 10 Feb 2025
Exploring RWKV for Memory Efficient and Low Latency Streaming ASR Keyu An Shiliang Zhang 18 4 0 26 Sep 2023
Trainability, Expressivity and Interpretability in Gated Neural ODEs T. Kim T. Can K. Krishnamurthy AI4CE 32 4 0 12 Jul 2023
General-Purpose In-Context Learning by Meta-Learning Transformers Louis Kirsch James Harrison Jascha Narain Sohl-Dickstein Luke Metz 29 72 0 08 Dec 2022
Criteria for Classifying Forecasting Methods Tim Januschowski Jan Gasthaus Bernie Wang David Salinas Valentin Flunkert Michael Bohlke-Schneider Laurent Callot AI4TS 16 173 0 07 Dec 2022
TeKo: Text-Rich Graph Neural Networks with External Knowledge Zhizhi Yu Di Jin Jianguo Wei Ziyang Liu Yue Shang Yun Xiao Jiawei Han Lingfei Wu 19 4 0 15 Jun 2022
Training neural networks using Metropolis Monte Carlo and an adaptive variant S. Whitelam V. Selin Ian Benlolo Corneel Casert Isaac Tamblyn BDL 11 7 0 16 May 2022
Intelligent Acoustic Module for Autonomous Vehicles using Fast Gated Recurrent approach Raghav Rawat Shreyash Gupta Shreyas Mohapatra S. P. Mishra Sreesankar Rajagopal 25 2 0 06 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 28 92 0 10 Nov 2021
Understanding How Encoder-Decoder Architectures Attend Kyle Aitken V. Ramasesh Yuan Cao Niru Maheswaranathan 18 17 0 28 Oct 2021
Is it enough to optimize CNN architectures on ImageNet? Lukas Tuggener Jürgen Schmidhuber Thilo Stadelmann 22 23 0 16 Mar 2021
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 48 669 0 06 Nov 2020
Unfolding recurrence by Green's functions for optimized reservoir computing Sandra Nestler Christian Keup David Dahmen M. Gilson Holger Rauhut M. Helias 6 4 0 13 Oct 2020
How recurrent networks implement contextual processing in sentiment analysis Niru Maheswaranathan David Sussillo 14 22 0 17 Apr 2020
Actor-Transformers for Group Activity Recognition Kirill Gavrilyuk Ryan Sanford Mehrsan Javan Cees G. M. Snoek ViT 19 178 0 28 Mar 2020
Capacity, Bandwidth, and Compositionality in Emergent Language Learning Cinjon Resnick Abhinav Gupta Jakob N. Foerster Andrew M. Dai Kyunghyun Cho 18 51 0 24 Oct 2019
Deep Temporal Analysis for Non-Acted Body Affect Recognition D. Avola Luigi Cinque Alessio Fagioli G. Foresti Cristiano Massaroni CVBM 28 27 0 23 Jul 2019
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics Niru Maheswaranathan Alex H. Williams Matthew D. Golub Surya Ganguli David Sussillo 13 77 0 25 Jun 2019
On Network Design Spaces for Visual Recognition Ilija Radosavovic Justin Johnson Saining Xie Wan-Yen Lo Piotr Dollár 9 134 0 30 May 2019
An Optimized Recurrent Unit for Ultra-Low-Power Keyword Spotting Justice Amoh K. Odame 24 17 0 13 Feb 2019
Deep Learning Scaling is Predictable, Empirically Joel Hestness Sharan Narang Newsha Ardalani G. Diamos Heewoo Jun Hassan Kianinejad Md. Mostofa Ali Patwary Yang Yang Yanqi Zhou 40 710 0 01 Dec 2017