Meta Learning Backpropagation And Improving It

29 December 2020

Papers citing "Meta Learning Backpropagation And Improving It"

43 / 43 papers shown

Title
Bio-Inspired Plastic Neural Networks for Zero-Shot Out-of-Distribution Generalization in Complex Animal-Inspired Robots Binggwong Leung Worasuchad Haomachai J. Pedersen S. Risi Poramate Manoonpong OODD 71 0 0 16 Mar 2025
Discovering Quality-Diversity Algorithms via Meta-Black-Box Optimization Maxence Faldor Robert Tjarko Lange Antoine Cully 71 0 0 04 Feb 2025
JaxLife: An Open-Ended Agentic Simulator Chris Xiaoxuan Lu Michael Beukman Michael T. Matthews Jakob Foerster LM&Ro 35 2 0 01 Sep 2024
Learning to (Learn at Test Time): RNNs with Expressive Hidden States Yu Sun Xinhao Li Karan Dalal Jiarui Xu Arjun Vikram ... Xinlei Chen Xiaolong Wang Sanmi Koyejo Tatsunori Hashimoto Carlos Guestrin 58 93 0 05 Jul 2024
Benchmarking General-Purpose In-Context Learning Fan Wang Chuan Lin Yang Cao Yu Kang 30 1 0 27 May 2024
FFCL: Forward-Forward Net with Cortical Loops, Training and Inference on Edge Without Backpropagation Ali Karkehabadi Houman Homayoun Avesta Sasan 24 9 0 21 May 2024
Structurally Flexible Neural Networks: Evolving the Building Blocks for General Agents J. Pedersen Erwan Plantec Eleni Nisioti Milton L. Montero Sebastian Risi 36 1 0 06 Apr 2024
Language Agents as Optimizable Graphs Mingchen Zhuge Wenyi Wang Louis Kirsch Francesco Faccio Dmitrii Khizbullin Jürgen Schmidhuber LLMAG 29 19 0 26 Feb 2024
Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Jackson Chris Xiaoxuan Lu Louis Kirsch R. T. Lange Shimon Whiteson Jakob N. Foerster 19 18 0 08 Feb 2024
Universal Neural Functionals Allan Zhou Chelsea Finn James Harrison 27 12 0 07 Feb 2024
Are LSTMs Good Few-Shot Learners? Mike Huisman Thomas M. Moerland Aske Plaat Jan N. van Rijn VLM 16 7 0 22 Oct 2023
Learning to (Learn at Test Time) Yu Sun Xinhao Li Karan Dalal Chloe Hsu Oluwasanmi Koyejo Carlos Guestrin Xiaolong Wang Tatsunori Hashimoto Xinlei Chen SSL 30 6 0 20 Oct 2023
The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute Aleksandar Stanić Dylan R. Ashley Oleg Serikov Louis Kirsch Francesco Faccio Jürgen Schmidhuber Thomas Hofmann Imanol Schlag MoE 38 9 0 20 Sep 2023
Understanding Catastrophic Forgetting in Language Models via Implicit Inference Suhas Kotha Jacob Mitchell Springer Aditi Raghunathan CLL 28 58 0 18 Sep 2023
Extending the Forward Forward Algorithm Saumya Gandhi Ritu Gala Jonah Kornberg Advaith Sridhar 25 6 0 09 Jul 2023
Brain-inspired learning in artificial neural networks: a review Samuel Schmidgall Jascha Achterberg Thomas Miconi Louis Kirsch Rojin Ziaei S. P. Hajiseyedrazi Jason Eshraghian 28 52 0 18 May 2023
Meta-Learned Models of Cognition Marcel Binz Ishita Dasgupta A. Jagadish M. Botvinick Jane X. Wang Eric Schulz 28 24 0 12 Apr 2023
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization R. T. Lange Tom Schaul Yutian Chen Chris Xiaoxuan Lu Tom Zahavy Valentin Dalibard Sebastian Flennerhag 24 34 0 08 Apr 2023
Learning Functional Transduction Mathieu Chalvidal Thomas Serre Rufin VanRullen AI4CE 30 2 0 01 Feb 2023
Transformers as Algorithms: Generalization and Stability in In-context Learning Yingcong Li M. E. Ildiz Dimitris Papailiopoulos Samet Oymak 18 152 0 17 Jan 2023
Eliminating Meta Optimization Through Self-Referential Meta Learning Louis Kirsch Jürgen Schmidhuber 23 7 0 29 Dec 2022
Learning One Abstract Bit at a Time Through Self-Invented Experiments Encoded as Neural Networks Vincent Herrmann Louis Kirsch Jürgen Schmidhuber AI4CE 38 4 0 29 Dec 2022
Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers Damai Dai Yutao Sun Li Dong Y. Hao Shuming Ma Zhifang Sui Furu Wei LRM 15 147 0 20 Dec 2022
Transformers learn in-context by gradient descent J. Oswald Eyvind Niklasson E. Randazzo João Sacramento A. Mordvintsev A. Zhmoginov Max Vladymyrov MLT 28 427 0 15 Dec 2022
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
Learning to Optimize with Dynamic Mode Decomposition Petr Simánek Daniel Vasata Pavel Kordík 31 5 0 29 Nov 2022
What learning algorithm is in-context learning? Investigations with linear models Ekin Akyürek Dale Schuurmans Jacob Andreas Tengyu Ma Denny Zhou 29 437 0 28 Nov 2022
Discovering Evolution Strategies via Meta-Black-Box Optimization R. T. Lange Tom Schaul Yutian Chen Tom Zahavy Valenti Dallibard Chris Xiaoxuan Lu Satinder Singh Sebastian Flennerhag 36 47 0 21 Nov 2022
Learning to Control Rapidly Changing Synaptic Connections: An Alternative Type of Memory in Sequence Processing Artificial Neural Networks Kazuki Irie Jürgen Schmidhuber KELM 16 1 0 17 Nov 2022
Discovered Policy Optimisation Chris Xiaoxuan Lu J. Kuba Alistair Letcher Luke Metz Christian Schroeder de Witt Jakob N. Foerster OffRL 31 74 0 11 Oct 2022
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 21 447 0 01 Aug 2022
Goal-Conditioned Generators of Deep Policies Francesco Faccio Vincent Herrmann Aditya A. Ramesh Louis Kirsch Jürgen Schmidhuber OffRL 25 8 0 04 Jul 2022
A Modern Self-Referential Weight Matrix That Learns to Modify Itself Kazuki Irie Imanol Schlag Róbert Csordás Jürgen Schmidhuber 14 26 0 11 Feb 2022
A Simple Guard for Learned Optimizers Isabeau Prémont-Schwarz Jaroslav Vítkru Jan Feyereisl 46 7 0 28 Jan 2022
Collective Intelligence for Deep Learning: A Survey of Recent Developments David R Ha Yu Tang AI4CE 23 68 0 29 Nov 2021
Parameter Prediction for Unseen Deep Architectures Boris Knyazev M. Drozdzal Graham W. Taylor Adriana Romero Soriano OOD 22 78 0 25 Oct 2021
Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch Sebastian Flennerhag Hado van Hasselt A. Friesen Junhyuk Oh Yutian Chen 15 30 0 22 Sep 2021
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning Fan Wang Hao Tian Haoyi Xiong Hua-Hong Wu Jie Fu Yang Cao Yu Kang Haifeng Wang AI4CE 15 3 0 08 Sep 2021
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning Yujin Tang David R Ha 22 75 0 07 Sep 2021
Meta-Learning Bidirectional Update Rules Mark Sandler Max Vladymyrov A. Zhmoginov Nolan Miller Andrew Jackson T. Madams Blaise Agüera y Arcas 13 15 0 10 Apr 2021
Linear Transformers Are Secretly Fast Weight Programmers Imanol Schlag Kazuki Irie Jürgen Schmidhuber 17 221 0 22 Feb 2021
Finding online neural update rules by learning to remember Karol Gregor CLL 34 6 0 06 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 314 11,681 0 09 Mar 2017