Unbiasing Truncated Backpropagation Through Time

23 May 2017

Papers citing "Unbiasing Truncated Backpropagation Through Time"

23 / 23 papers shown

Title
Density Matrix Emulation of Quantum Recurrent Neural Networks for Multivariate Time Series Prediction José Daniel Viqueira Daniel Faílde M. M. Juane Andrés Gómez David Mera 30 5 0 31 Oct 2023
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies Oscar Li James Harrison Jascha Narain Sohl-Dickstein Virginia Smith Luke Metz 56 5 0 21 Apr 2023
Deep Subspace Encoders for Nonlinear System Identification G. Beintema Maarten Schoukens R. Tóth 30 34 0 26 Oct 2022
Theseus: A Library for Differentiable Nonlinear Optimization Luis Pineda Taosha Fan Maurizio Monge S. Venkataraman Paloma Sodhi ... Austin S. Wang Stuart Anderson Jing Dong Brandon Amos Mustafa Mukadam 34 76 0 19 Jul 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 55 151 0 01 Jun 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 47 19 0 13 Mar 2022
Tutorial on amortized optimization Brandon Amos OffRL 78 43 0 01 Feb 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 27 68 0 27 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 30 93 0 10 Nov 2021
Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation C. Freeman Erik Frey Anton Raichuk Sertan Girgin Igor Mordatch Olivier Bachem 48 355 0 24 Jun 2021
Non-Autoregressive vs Autoregressive Neural Networks for System Identification Daniel Weber C. Gühmann 27 7 0 05 May 2021
RIANN -- A Robust Neural Network Outperforms Attitude Estimation Filters Daniel Weber C. Gühmann Thomas Seel 23 35 0 15 Apr 2021
A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound A. Stanziola Simon Arridge B. Cox B. Treeby 16 32 0 29 Oct 2020
Training Stronger Baselines for Learning to Optimize Tianlong Chen Weiyi Zhang Jingyang Zhou Shiyu Chang Sijia Liu Lisa Amini Zhangyang Wang OffRL 27 51 0 18 Oct 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 35 62 0 23 Sep 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 34 7 0 05 Jun 2020
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias Christopher Aicher N. Foti E. Fox MQ 30 32 0 17 May 2019
Learning Discrete Structures for Graph Neural Networks Luca Franceschi Mathias Niepert Massimiliano Pontil X. He GNN 30 410 0 28 Mar 2019
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning Frederik Benzing M. Gauy Asier Mujika A. Martinsson Angelika Steger 23 22 0 11 Feb 2019
Approximating Real-Time Recurrent Learning with Random Kronecker Factors Asier Mujika Florian Meier Angelika Steger 19 61 0 28 May 2018
Reviving and Improving Recurrent Back-Propagation Renjie Liao Yuwen Xiong Ethan Fetaya Lisa Zhang Kijung Yoon Xaq Pitkow R. Urtasun R. Zemel BDL 44 118 0 16 Mar 2018
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks Nan Rosemary Ke Anirudh Goyal O. Bilaniuk Jonathan Binas Laurent Charlin C. Pal Yoshua Bengio 35 15 0 07 Nov 2017
Regularizing and Optimizing LSTM Language Models Stephen Merity N. Keskar R. Socher 95 1,091 0 07 Aug 2017