brain imitation learning tag

Gwern Branwen

See Also
Gwern
- “Modular Brain AUNNs for Uploads”, Gwern 2023
- “WBE and DRL: a Middle Way of Imitation Learning from the Human Brain”, Gwern 2018
Links
Miscellaneous
Link Bibliography

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Gwern

“Modular Brain AUNNs for Uploads”, Gwern 2023

Modular Brain AUNNs for Uploads

“WBE and DRL: a Middle Way of Imitation Learning from the Human Brain”, Gwern 2018

WBE and DRL: a Middle Way of imitation learning from the human brain

Links

“Instruction-Tuning Aligns LLMs to the Human Brain”, Aw et al 2023

Instruction-tuning Aligns LLMs to the Human Brain

“Improving Neural Network Representations Using Human Similarity Judgments”, Muttenthaler et al 2023

Improving neural network representations using human similarity judgments

“Performance Reserves in Brain-Imaging-Based Phenotype Prediction”, Schulz et al 2022

Performance reserves in brain-imaging-based phenotype prediction

“Brains and Algorithms Partially Converge in Natural Language Processing”, Caucheteux & King 2022

Brains and algorithms partially converge in natural language processing

“Generative Models of Brain Dynamics—A Review”, Panahi et al 2021

Generative Models of Brain Dynamics—A review

“Toward Conceptual Networks in Brain: Decoding Imagined Words from Word Reading”, He et al 2021

Toward Conceptual Networks in Brain: Decoding Imagined Words from Word Reading

“In Vitro Neurons Learn and Exhibit Sentience When Embodied in a Simulated Game-World”, Kagan et al 2021

In vitro neurons learn and exhibit sentience when embodied in a simulated game-world

“Long-Range and Hierarchical Language Predictions in Brains and Algorithms”, Caucheteux et al 2021

Long-range and hierarchical language predictions in brains and algorithms

“Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, Harrington & Deza 2021

Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks

“Fine-Tuning of Deep Language Models As a Computational Framework of Modeling Listeners’ Perspective during Language Comprehension”, Tikochinski et al 2021

Fine-tuning of deep language models as a computational framework of modeling listeners’ perspective during language comprehension

“Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks”, Ericsson et al 2021

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks

“Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies”, Plas et al 2021

Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

“Unsupervised Deep Learning Identifies Semantic Disentanglement in Single Inferotemporal Face Patch Neurons”, Higgins et al 2021

Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons

“Your Head Is There to Move You Around: Goal-Driven Models of the Primate Dorsal Pathway”, Mineault et al 2021

Your head is there to move you around: Goal-driven models of the primate dorsal pathway

“Deep Learning Models of Cognitive Processes Constrained by Human Brain Connectomes”, Zhang et al 2021

Deep learning models of cognitive processes constrained by human brain connectomes

“Monkey Plays Pac-Man With Compositional Strategies and Hierarchical Decision-Making”, Yang et al 2021

Monkey Plays Pac-Man with Compositional Strategies and Hierarchical Decision-making

“Text2Brain: Synthesis of Brain Activation Maps from Free-Form Text Query”, Ngo et al 2021

Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query

“Capturing the Objects of Vision With Neural Networks”, Peters & Kriegeskorte 2021

Capturing the objects of vision with neural networks

“Fitting Summary Statistics of Neural Data With a Differentiable Spiking Network Simulator”, Bellec et al 2021

Fitting summary statistics of neural data with a differentiable spiking network simulator

“The Functional Specialization of Visual Cortex Emerges from Training Parallel Pathways With Self-Supervised Predictive Learning”, Bakhtiari et al 2021

The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning

“Embracing New Techniques in Deep Learning for Estimating Image Memorability”, Needell & Bainbridge 2021

Embracing New Techniques in Deep Learning for Estimating Image Memorability

“A Massive 7T FMRI Dataset to Bridge Cognitive and Computational Neuroscience”, Allen et al 2021

A massive 7T fMRI dataset to bridge cognitive and computational neuroscience

“Brain-Computer Interface for Generating Personally Attractive Images”, Spape et al 2021

Brain-computer interface for generating personally attractive images

“BENDR: Using Transformers and a Contrastive Self-Supervised Learning Task to Learn from Massive Amounts of EEG Data”, Kostas et al 2021

BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data

“Selective Eye-Gaze Augmentation To Enhance Imitation Learning In Atari Games”, Thammineni et al 2020

Selective Eye-gaze Augmentation To Enhance Imitation Learning In Atari Games

“MoGaze: A Dataset of Full-Body Motions That Includes Workspace Geometry and Eye-Gaze”, Kratzer et al 2020

MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze

“The Hearing Aid Dilemma: Amplification, Compression, and Distortion of the Neural Code”, Armstrong et al 2020

The hearing aid dilemma: amplification, compression, and distortion of the neural code

“Self-Supervised Natural Image Reconstruction and Rich Semantic Classification from Brain Activity”, Gaziv et al 2020

Self-Supervised Natural Image Reconstruction and Rich Semantic Classification from Brain Activity

“Self-Supervised Learning through the Eyes of a Child”, Orhan et al 2020

Self-supervised learning through the eyes of a child

“Deep Neural Network Models of Sound Localization Reveal How Perception Is Adapted to Real-World Environments”, Francl & McDermott 2020

Deep neural network models of sound localization reveal how perception is adapted to real-world environments

“What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking”, Kröger et al 2020

What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking

“Inducing Brain-Relevant Bias in Natural Language Processing Models”, Schwartz et al 2019

Inducing brain-relevant bias in natural language processing models

“Low-Dimensional Embodied Semantics for Music and Language”, Raposo et al 2019

Low-dimensional Embodied Semantics for Music and Language

“Improved Object Recognition Using Neural Networks Trained to Mimic the Brain’s Statistical Properties”, Federer et al 2019

Improved object recognition using neural networks trained to mimic the brain’s statistical properties

“Neural System Identification With Neural Information Flow”, Seeliger et al 2019

Neural System Identification with Neural Information Flow

“Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”, Zhang et al 2019

Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset

“Neural Population Control via Deep Image Synthesis”, Bashivan et al 2019

Neural population control via deep image synthesis

“Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”, Palazzo et al 2018

Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features

“Humans Can Decipher Adversarial Images”, Zhou & Firestone 2018

Humans can decipher adversarial images

“A Neurobiological Evaluation Metric for Neural Network Model Search”, Blanchard et al 2018

A Neurobiological Evaluation Metric for Neural Network Model Search

“Visceral Machines: Risk-Aversion in Reinforcement Learning With Intrinsic Physiological Rewards”, McDuff & Kapoor 2018

Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards

“Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-Of-The-Art Deep Artificial Neural Networks”, Rajalingham et al 2018

Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks

“Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Raposo et al 2017

Towards Deep Modeling of Music Semantics using EEG Regularizers

“Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction”, Lathuilière et al 2017

Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction

“Predicting Driver Attention in Critical Situations”, Xia et al 2017

Predicting Driver Attention in Critical Situations

“The Signature of Robot Action Success in EEG Signals of a Human Observer: Decoding and Visualization Using Deep Convolutional Neural Networks”, Behncke et al 2017

The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks

“Towards Personalized Human AI Interaction—Adapting the Behavior of AI Agents Using Neural Signatures of Subjective Interest”, Shih et al 2017

Towards personalized human AI interaction—adapting the behavior of AI agents using neural signatures of subjective interest

“Brain Responses During Robot-Error Observation”, Welke et al 2017

Brain Responses During Robot-Error Observation

“Using Human Brain Activity to Guide Machine Learning”, Fong et al 2017

Using Human Brain Activity to Guide Machine Learning

“Mapping Between FMRI Responses to Movies and Their Natural Language Annotations”, Vodrahalli et al 2016

Mapping Between fMRI Responses to Movies and their Natural Language Annotations

“Deep Learning Human Mind for Automated Visual Classification”, Spampinato et al 2016

Deep Learning Human Mind for Automated Visual Classification

“Towards an Integration of Deep Learning and Neuroscience”, Marblestone et al 2016

Towards an integration of deep learning and neuroscience

“Improving Sentence Compression by Learning to Predict Gaze”, Klerke et al 2016

Improving sentence compression by learning to predict gaze

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