“Performance Reserves in Brain-imaging-based Phenotype Prediction”, Schulz Et Al 2022

“Performance reserves in brain-imaging-based phenotype prediction”⁠, Marc-Andre Schulz, Danilo Bzdok, Stefan Haufe, John-Dylan Haynes, Kerstin Ritter2022-02-25 (AI scaling⁠, neuroscience; similar)

“Brains and Algorithms Partially Converge in Natural Language Processing”, Caucheteux & King2022

“Brains and algorithms partially converge in natural language processing”⁠, Charlotte Caucheteux, Jean-Rémi King2022-02-16 (GPT⁠, AI scaling⁠, neuroscience; similar; bibliography)

“Generative Models of Brain Dynamics—A Review”, Panahi Et Al 2021

“Generative Models of Brain Dynamics—A review”⁠, Mahta Ramezanian Panahi, Germán Abrevaya, Jean-Christophe Gagnon-Audet, Vikram Voleti, Irina Rish, Guillaume Dumas2021-12-22 (neuroscience; similar)

“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”⁠, Linyang He, Shujie Geng, Jiawei Han, Miao Cao, Jianfeng Feng2021-12-11 (neuroscience; similar)

“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”⁠, Brett J. Kagan, Andy C. Kitchen, Nhi T. Tran, Bradyn J. Parker, Anjali Bhat, Ben Rollo, Adeel Razi, Karl J. Friston2021-12-03 (neuroscience; similar)

“Long-range and Hierarchical Language Predictions in Brains and Algorithms”, Caucheteux Et Al 2021

“Long-range and hierarchical language predictions in brains and algorithms”⁠, Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King2021-11-28 (GPT⁠, neuroscience; similar)

“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”⁠, Refael Tikochinski, Ariel Goldstein, Yaara Yeshurun, Uri Hasson, Roi Reichart2021-11-23 (neuroscience; similar)

“Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, Harrington & Deza2021

“Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”⁠, Anne Harrington, Arturo Deza2021-11-23 (neural net/adversarial/human⁠, neuroscience; similar)

“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”⁠, Linus Ericsson, Henry Gouk, Timothy M. Hospedales2021-11-22 (neural net⁠, neuroscience; similar)

“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”⁠, Thijs L. van der Plas, Jérôme Tubiana, Guillaume Le Goc, Geoffrey Migault, Michael Kunst, Herwig Baier2021-11-11 (neuroscience; similar)

“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”⁠, Irina Higgins, Le Chang, Victoria Langston, Demis Hassabis, Christopher Summerfield, Doris Tsao, Matthew Botvinick2021-11-09 (autoencoder NN⁠, neuroscience; similar)

“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”⁠, Patrick J. Mineault, Shahab Bakhtiari, Blake A. Richards, Christopher C. Pack2021-10-26 (neuroscience; similar)

“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”⁠, Yu Zhang, Nicolas Farrugia, Pierre Bellec2021-10-14 (CNN⁠, neuroscience; similar)

“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”⁠, Qianli Yang, Zhongqiao Lin, Wenyi Zhang, Jianshu Li, Xiyuan Chen, Jiaqi Zhang, Tianming Yang2021-10-04 (neuroscience⁠, RL exploration; similar)

“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”⁠, Gia H. Ngo, Minh Nguyen, Nancy F. Chen, Mert R. Sabuncu2021-09-28 (Transformer NN⁠, neuroscience; similar)

“Capturing the Objects of Vision With Neural Networks”, Peters & Kriegeskorte2021

“Capturing the objects of vision with neural networks”⁠, Benjamin Peters, Nikolaus Kriegeskorte2021-09-07 (neuroscience; similar)

“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”⁠, Shahab Bakhtiari, Patrick Mineault, Tim Lillicrap, Christopher C. Pack, Blake A. Richards2021-06-18 (neuroscience; similar)

“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”⁠, Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner2021-06-18 (neuroscience; similar)

“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”⁠, Emily Jean Allen, Ghislain St-Yves, Yihan Wu, Jesse L. Breedlove, Logan T. Dowdle, Bradley Caron, Franco Pestilli2021-02-22 (ML dataset⁠, neuroscience; backlinks; similar)

“Brain-computer Interface for Generating Personally Attractive Images”, Spape Et Al 2021

“Brain-computer interface for generating personally attractive images”⁠, Michiel Spape, Keith M. Davis III, Lauri Kangassalo, Niklas Ravaja, Zania Sovijarvi-Spape, Tuukka Ruotsalo2021-02-12 (StyleGAN/progan⁠, preference learning; similar)

“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”⁠, Demetres Kostas, Stephane Aroca-Ouellette, Frank Rudzicz2021-01-28 (Transformer NN⁠, neuroscience; similar)

“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”⁠, Chaitanya Thammineni, Hemanth Manjunatha, Ehsan T. Esfahani2020-12-05 (neural net; similar)

“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”⁠, Philipp Kratzer, Simon Bihlmaier, Niteesh Balachandra Midlagajni, Rohit Prakash, Marc Toussaint, Jim Mainprice2020-11-23 (robotics; similar)

“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”⁠, Alex Armstrong, Chi Chung Lam, Shievanie Sabesan, Nicholas A. Lesica2020-10-04 (neuroscience; similar)

“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”⁠, Guy Gaziv, Roman Beliy, Niv Granot, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani2020-09-08 (similar)

“Self-supervised Learning through the Eyes of a Child”, Orhan Et Al 2020

“Self-supervised learning through the eyes of a child”⁠, A. Emin Orhan, Vaibhav V. Gupta, Brenden M. Lake2020-07-31 (AI scaling⁠, video analysis; similar)

“Deep Neural Network Models of Sound Localization Reveal How Perception Is Adapted to Real-world Environments”, Francl & McDermott2020

“Deep neural network models of sound localization reveal how perception is adapted to real-world environments”⁠, Andrew Francl, Josh H. McDermott2020-07-22 (neuroscience; similar)

“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”⁠, Jacob Leon Kröger, Otto Hans-Martin Lutz, Florian Müller2020-03-20 (personality⁠, tech; backlinks; similar)

“Inducing Brain-relevant Bias in Natural Language Processing Models”, Schwartz Et Al 2019

“Inducing brain-relevant bias in natural language processing models”⁠, Dan Schwartz, Mariya Toneva, Leila Wehbe2019-10-29 (similar)

“Low-dimensional Embodied Semantics for Music and Language”, Raposo Et Al 2019

“Low-dimensional Embodied Semantics for Music and Language”⁠, Francisco Afonso Raposo, David Martins de Matos, Ricardo Ribeiro2019-06-20 (AI/music; similar)

“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”⁠, Callie Federer, Haoyan Xu, Alona Fyshe, Joel Zylberberg2019-05-25 (CNN⁠, neuroscience; similar)

“Neural System Identification With Neural Information Flow”, Seeliger Et Al 2019

“Neural System Identification with Neural Information Flow”⁠, Katja Seeliger, Luca Ambrogioni, Yağmur Güçlütürk, Umut Güçlü, Marcel A. J. van Gerven2019-05-23 (CNN; similar)

“Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”, Zhang Et Al 2019

“Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”⁠, Ruohan Zhang, Calen Walshe, Zhuode Liu, Lin Guan, Karl S. Muller, Jake A. Whritner, Luxin Zhang, Mary M. Hayhoe2019-03-15 (neuroscience; similar)

“Neural Population Control via Deep Image Synthesis”, Bashivan Et Al 2019

“Neural population control via deep image synthesis”⁠, Pouya Bashivan, Kohitij Kar, James J. DiCarlo2019 (neural net/adversarial/human⁠, neuroscience; similar)

“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”⁠, Simone Palazzo, Concetto Spampinato, Isaak Kavasidis, Daniela Giordano, Joseph Schmidt, Mubarak Shah2018-10-25 (similar)

“WBE and DRL: a Middle Way of Imitation Learning from the Human Brain”, Branwen2018

“WBE and DRL: a Middle Way of imitation learning from the human brain”⁠, Gwern Branwen2018-10-20 (AI scaling⁠, meta-learning; backlinks; similar)

“Humans Can Decipher Adversarial Images”, Zhou & Firestone2018

“Humans can decipher adversarial images”⁠, Zhenglong Zhou, Chaz Firestone2018-09-11 (neural net/adversarial/human⁠, neuroscience; similar)

“A Neurobiological Evaluation Metric for Neural Network Model Search”, Blanchard Et Al 2018

“A Neurobiological Evaluation Metric for Neural Network Model Search”⁠, Nathaniel Blanchard, Jeffery Kinnison, Brandon RichardWebster, Pouya Bashivan, Walter J. Scheirer2018-05-28 (similar)

“Visceral Machines: Risk-Aversion in Reinforcement Learning With Intrinsic Physiological Rewards”, McDuff & Kapoor2018

“Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards”⁠, Daniel McDuff, Ashish Kapoor2018-05-25 (AI safety; similar)

“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”⁠, Rishi Rajalingham, Elias B. Issa, Pouya Bashivan, Kohitij Kar, Kailyn Schmidt, James J. DiCarlo2018-02-12 (CNN⁠, neuroscience; similar)

“Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Raposo Et Al 2017

“Towards Deep Modeling of Music Semantics using EEG Regularizers”⁠, Francisco Raposo, David Martins de Matos, Ricardo Ribeiro, Suhua Tang, Yi Yu2017-12-14 (AI/music⁠, retrieval AI; similar)

“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”⁠, Stéphane Lathuilière, Benoit Massé, Pablo Mesejo, Radu Horaud2017-11-18 (robotics; similar)

“Predicting Driver Attention in Critical Situations”, Xia Et Al 2017

“Predicting Driver Attention in Critical Situations”⁠, Ye Xia, Danqing Zhang, Jinkyu Kim, Ken Nakayama, Karl Zipser, David Whitney2017-11-17 (similar)

“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”⁠, Joos Behncke, Robin Tibor Schirrmeister, Wolfram Burgard, Tonio Ball2017-11-16 (CNN⁠, robotics; similar)

“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”⁠, Victor Shih, David C. Jangraw, Paul Sajda, Sameer Saproo2017-09-14 (preference learning; similar)

“Brain Responses During Robot-Error Observation”, Welke Et Al 2017

“Brain Responses During Robot-Error Observation”⁠, Dominik Welke, Joos Behncke, Marina Hader, Robin Tibor Schirrmeister, Andreas Schönau, Boris Eßmann, Oliver Müller2017-08-04 (robotics; similar)

“Using Human Brain Activity to Guide Machine Learning”, Fong Et Al 2017

“Using Human Brain Activity to Guide Machine Learning”⁠, Ruth Fong, Walter Scheirer, David Cox2017-03-16 (CNN; similar)

“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”⁠, Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Christopher Baldassano, Janice Chen, Esther Yong, Christopher Honey2016-10-13 (similar)

“Deep Learning Human Mind for Automated Visual Classification”, Spampinato Et Al 2016

“Deep Learning Human Mind for Automated Visual Classification”⁠, Concetto Spampinato, Simone Palazzo, Isaak Kavasidis, Daniela Giordano, Mubarak Shah, Nasim Souly2016-09-01 (CNN⁠, RNN⁠, neuroscience; similar)

“Towards an Integration of Deep Learning and Neuroscience”, Marblestone Et Al 2016

“Towards an integration of deep learning and neuroscience”⁠, Adam H. Marblestone, Greg Wayne, Konrad P. Kording2016-08-22 (neuroscience; similar)

“Improving Sentence Compression by Learning to Predict Gaze”, Klerke Et Al 2016

“Improving sentence compression by learning to predict gaze”⁠, Sigrid Klerke, Yoav Goldberg, Anders Søgaard2016-04-12 (RNN⁠, neuroscience)

Wikipedia

1. Lexical hypothesis