Unbiasing Truncated Backpropagation Through Time

23 May 2017

Papers citing "Unbiasing Truncated Backpropagation Through Time"

20 / 20 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 28 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 49 5 0 21 Apr 2023
Deep Subspace Encoders for Nonlinear System Identification G. Beintema Maarten Schoukens R. Tóth 14 33 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 26 76 0 19 Jul 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 41 149 0 01 Jun 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 45 19 0 13 Mar 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 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 67 0 27 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 28 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 48 350 0 24 Jun 2021
Non-Autoregressive vs Autoregressive Neural Networks for System Identification Daniel Weber C. Gühmann 19 7 0 05 May 2021
RIANN -- A Robust Neural Network Outperforms Attitude Estimation Filters Daniel Weber C. Gühmann Thomas Seel 12 35 0 15 Apr 2021
Training Stronger Baselines for Learning to Optimize Tianlong Chen Weiyi Zhang Jingyang Zhou Shiyu Chang Sijia Liu Lisa Amini Zhangyang Wang OffRL 25 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 33 62 0 23 Sep 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias Christopher Aicher N. Foti E. Fox MQ 22 32 0 17 May 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 11 60 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 36 118 0 16 Mar 2018
Regularizing and Optimizing LSTM Language Models Stephen Merity N. Keskar R. Socher 60 1,091 0 07 Aug 2017