- See Also
-
Links
- “Performance Reserves in Brain-imaging-based Phenotype Prediction”, Et Al 2022
- “Brains and Algorithms Partially Converge in Natural Language Processing”, 2022
- “Generative Models of Brain Dynamics—A Review”, Et Al 2021
- “Toward Conceptual Networks in Brain: Decoding Imagined Words from Word Reading”, Et Al 2021
- “In Vitro Neurons Learn and Exhibit Sentience When Embodied in a Simulated Game-world”, Et Al 2021
- “Long-range and Hierarchical Language Predictions in Brains and Algorithms”, Et Al 2021
- “Fine-tuning of Deep Language Models As a Computational Framework of Modeling Listeners’ Perspective during Language Comprehension”, Et Al 2021
- “Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, 2021
- “Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks”, Et Al 2021
- “Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies”, Et Al 2021
- “Unsupervised Deep Learning Identifies Semantic Disentanglement in Single Inferotemporal Face Patch Neurons”, Et Al 2021
- “Your Head Is There to Move You Around: Goal-driven Models of the Primate Dorsal Pathway”, Et Al 2021
- “Deep Learning Models of Cognitive Processes Constrained by Human Brain Connectomes”, Et Al 2021
- “Monkey Plays Pac-Man With Compositional Strategies and Hierarchical Decision-making”, Et Al 2021
- “Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query”, Et Al 2021
- “Capturing the Objects of Vision With Neural Networks”, 2021
- “The Functional Specialization of Visual Cortex Emerges from Training Parallel Pathways With Self-supervised Predictive Learning”, Et Al 2021
- “Fitting Summary Statistics of Neural Data With a Differentiable Spiking Network Simulator”, Et Al 2021
- “A Massive 7T FMRI Dataset to Bridge Cognitive and Computational Neuroscience”, Et Al 2021
- “Brain-computer Interface for Generating Personally Attractive Images”, Et Al 2021
- “BENDR: Using Transformers and a Contrastive Self-supervised Learning Task to Learn from Massive Amounts of EEG Data”, Et Al 2021
- “Selective Eye-gaze Augmentation To Enhance Imitation Learning In Atari Games”, Et Al 2020
- “MoGaze: A Dataset of Full-Body Motions That Includes Workspace Geometry and Eye-Gaze”, Et Al 2020
- “The Hearing Aid Dilemma: Amplification, Compression, and Distortion of the Neural Code”, Et Al 2020
- “Self-Supervised Natural Image Reconstruction and Rich Semantic Classification from Brain Activity”, Et Al 2020
- “Self-supervised Learning through the Eyes of a Child”, Et Al 2020
- “Deep Neural Network Models of Sound Localization Reveal How Perception Is Adapted to Real-world Environments”, Francl & 2020
- “What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking”, Et Al 2020
- “Inducing Brain-relevant Bias in Natural Language Processing Models”, Et Al 2019
- “Low-dimensional Embodied Semantics for Music and Language”, Et Al 2019
- “Improved Object Recognition Using Neural Networks Trained to Mimic the Brain’s Statistical Properties”, Et Al 2019
- “Neural System Identification With Neural Information Flow”, Et Al 2019
- “Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”, Et Al 2019
- “Neural Population Control via Deep Image Synthesis”, Et Al 2019
- “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”, Et Al 2018
- “WBE and DRL: a Middle Way of Imitation Learning from the Human Brain”, 2018
- “Humans Can Decipher Adversarial Images”, 2018
- “A Neurobiological Evaluation Metric for Neural Network Model Search”, Et Al 2018
- “Visceral Machines: Risk-Aversion in Reinforcement Learning With Intrinsic Physiological Rewards”, 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”, Et Al 2018
- “Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Et Al 2017
- “Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction”, Et Al 2017
- “Predicting Driver Attention in Critical Situations”, Et Al 2017
- “The Signature of Robot Action Success in EEG Signals of a Human Observer: Decoding and Visualization Using Deep Convolutional Neural Networks”, Et Al 2017
- “Towards Personalized Human AI Interaction—adapting the Behavior of AI Agents Using Neural Signatures of Subjective Interest”, Et Al 2017
- “Brain Responses During Robot-Error Observation”, Et Al 2017
- “Using Human Brain Activity to Guide Machine Learning”, Et Al 2017
- “Mapping Between FMRI Responses to Movies and Their Natural Language Annotations”, Et Al 2016
- “Deep Learning Human Mind for Automated Visual Classification”, Et Al 2016
- “Towards an Integration of Deep Learning and Neuroscience”, Et Al 2016
- “Improving Sentence Compression by Learning to Predict Gaze”, Et Al 2016
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Performance Reserves in Brain-imaging-based Phenotype Prediction”, Et Al 2022
“Performance reserves in brain-imaging-based phenotype prediction”, 2022-02-25 ( ; similar)
“Brains and Algorithms Partially Converge in Natural Language Processing”, 2022
“Brains and algorithms partially converge in natural language processing”, 2022-02-16 ( ; similar; bibliography)
“Generative Models of Brain Dynamics—A Review”, Et Al 2021
“Generative Models of Brain Dynamics—A review”, 2021-12-22 ( ; similar)
“Toward Conceptual Networks in Brain: Decoding Imagined Words from Word Reading”, Et Al 2021
“Toward Conceptual Networks in Brain: Decoding Imagined Words from Word Reading”, 2021-12-11 ( ; similar)
“In Vitro Neurons Learn and Exhibit Sentience When Embodied in a Simulated Game-world”, Et Al 2021
“In vitro neurons learn and exhibit sentience when embodied in a simulated game-world”, 2021-12-03 ( ; similar)
“Long-range and Hierarchical Language Predictions in Brains and Algorithms”, Et Al 2021
“Long-range and hierarchical language predictions in brains and algorithms”, 2021-11-28 ( ; similar)
“Fine-tuning of Deep Language Models As a Computational Framework of Modeling Listeners’ Perspective during Language Comprehension”, Et Al 2021
“Fine-tuning of deep language models as a computational framework of modeling listeners’ perspective during language comprehension”, 2021-11-23 ( ; similar)
“Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, 2021
“Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks”, 2021-11-23 ( ; similar)
“Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks”, Et Al 2021
“Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks”, 2021-11-22 ( ; similar)
“Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies”, Et Al 2021
“Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies”, 2021-11-11 ( ; similar)
“Unsupervised Deep Learning Identifies Semantic Disentanglement in Single Inferotemporal Face Patch Neurons”, Et Al 2021
“Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons”, 2021-11-09 ( ; similar)
“Your Head Is There to Move You Around: Goal-driven Models of the Primate Dorsal Pathway”, Et Al 2021
“Your head is there to move you around: Goal-driven models of the primate dorsal pathway”, 2021-10-26 ( ; similar)
“Deep Learning Models of Cognitive Processes Constrained by Human Brain Connectomes”, Et Al 2021
“Deep learning models of cognitive processes constrained by human brain connectomes”, 2021-10-14 ( ; similar)
“Monkey Plays Pac-Man With Compositional Strategies and Hierarchical Decision-making”, Et Al 2021
“Monkey Plays Pac-Man with Compositional Strategies and Hierarchical Decision-making”, 2021-10-04 ( ; similar)
“Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query”, Et Al 2021
“Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query”, 2021-09-28 ( ; similar)
“Capturing the Objects of Vision With Neural Networks”, 2021
“Capturing the objects of vision with neural networks”, 2021-09-07 ( ; similar)
“The Functional Specialization of Visual Cortex Emerges from Training Parallel Pathways With Self-supervised Predictive Learning”, Et Al 2021
“The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning”, 2021-06-18 ( ; similar)
“Fitting Summary Statistics of Neural Data With a Differentiable Spiking Network Simulator”, Et Al 2021
“Fitting summary statistics of neural data with a differentiable spiking network simulator”, 2021-06-18 ( ; similar)
“A Massive 7T FMRI Dataset to Bridge Cognitive and Computational Neuroscience”, Et Al 2021
“A massive 7T fMRI dataset to bridge cognitive and computational neuroscience”, 2021-02-22 ( ; backlinks; similar)
“Brain-computer Interface for Generating Personally Attractive Images”, Et Al 2021
“Brain-computer interface for generating personally attractive images”, 2021-02-12 ( ; similar)
“BENDR: Using Transformers and a Contrastive Self-supervised Learning Task to Learn from Massive Amounts of EEG Data”, Et Al 2021
“BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data”, 2021-01-28 ( ; similar)
“Selective Eye-gaze Augmentation To Enhance Imitation Learning In Atari Games”, Et Al 2020
“Selective Eye-gaze Augmentation To Enhance Imitation Learning In Atari Games”, 2020-12-05 ( ; similar)
“MoGaze: A Dataset of Full-Body Motions That Includes Workspace Geometry and Eye-Gaze”, Et Al 2020
“MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze”, 2020-11-23 ( ; similar)
“The Hearing Aid Dilemma: Amplification, Compression, and Distortion of the Neural Code”, Et Al 2020
“The hearing aid dilemma: amplification, compression, and distortion of the neural code”, 2020-10-04 ( ; similar)
“Self-Supervised Natural Image Reconstruction and Rich Semantic Classification from Brain Activity”, Et Al 2020
“Self-Supervised Natural Image Reconstruction and Rich Semantic Classification from Brain Activity”, 2020-09-08 (similar)
“Self-supervised Learning through the Eyes of a Child”, Et Al 2020
“Self-supervised learning through the eyes of a child”, 2020-07-31 ( ; similar)
“Deep Neural Network Models of Sound Localization Reveal How Perception Is Adapted to Real-world Environments”, Francl & 2020
“Deep neural network models of sound localization reveal how perception is adapted to real-world environments”, 2020-07-22 ( ; similar)
“What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking”, Et Al 2020
“What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking”, 2020-03-20 ( ; backlinks; similar)
“Inducing Brain-relevant Bias in Natural Language Processing Models”, Et Al 2019
“Inducing brain-relevant bias in natural language processing models”, 2019-10-29 (similar)
“Low-dimensional Embodied Semantics for Music and Language”, Et Al 2019
“Low-dimensional Embodied Semantics for Music and Language”, 2019-06-20 ( ; similar)
“Improved Object Recognition Using Neural Networks Trained to Mimic the Brain’s Statistical Properties”, Et Al 2019
“Improved object recognition using neural networks trained to mimic the brain’s statistical properties”, 2019-05-25 ( ; similar)
“Neural System Identification With Neural Information Flow”, Et Al 2019
“Neural System Identification with Neural Information Flow”, 2019-05-23 ( ; similar)
“Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”, Et Al 2019
“Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset”, 2019-03-15 ( ; similar)
“Neural Population Control via Deep Image Synthesis”, Et Al 2019
“Neural population control via deep image synthesis”, 2019 ( ; similar)
“Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”, Et Al 2018
“Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”, 2018-10-25 (similar)
“WBE and DRL: a Middle Way of Imitation Learning from the Human Brain”, 2018
“WBE and DRL: a Middle Way of imitation learning from the human brain”, 2018-10-20 ( ; backlinks; similar)
“Humans Can Decipher Adversarial Images”, 2018
“Humans can decipher adversarial images”, 2018-09-11 ( ; similar)
“A Neurobiological Evaluation Metric for Neural Network Model Search”, Et Al 2018
“A Neurobiological Evaluation Metric for Neural Network Model Search”, 2018-05-28 (similar)
“Visceral Machines: Risk-Aversion in Reinforcement Learning With Intrinsic Physiological Rewards”, 2018
“Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards”, 2018-05-25 ( ; 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”, 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”, 2018-02-12 ( ; similar)
“Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Et Al 2017
“Towards Deep Modeling of Music Semantics using EEG Regularizers”, 2017-12-14 ( ; similar)
“Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction”, Et Al 2017
“Neural Network Based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction”, 2017-11-18 ( ; similar)
“Predicting Driver Attention in Critical Situations”, Et Al 2017
“Predicting Driver Attention in Critical Situations”, 2017-11-17 (similar)
“The Signature of Robot Action Success in EEG Signals of a Human Observer: Decoding and Visualization Using Deep Convolutional Neural Networks”, Et Al 2017
“The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks”, 2017-11-16 ( ; similar)
“Towards Personalized Human AI Interaction—adapting the Behavior of AI Agents Using Neural Signatures of Subjective Interest”, Et Al 2017
“Towards personalized human AI interaction—adapting the behavior of AI agents using neural signatures of subjective interest”, 2017-09-14 ( ; similar)
“Brain Responses During Robot-Error Observation”, Et Al 2017
“Brain Responses During Robot-Error Observation”, 2017-08-04 ( ; similar)
“Using Human Brain Activity to Guide Machine Learning”, Et Al 2017
“Using Human Brain Activity to Guide Machine Learning”, 2017-03-16 ( ; similar)
“Mapping Between FMRI Responses to Movies and Their Natural Language Annotations”, Et Al 2016
“Mapping Between fMRI Responses to Movies and their Natural Language Annotations”, 2016-10-13 (similar)
“Deep Learning Human Mind for Automated Visual Classification”, Et Al 2016
“Deep Learning Human Mind for Automated Visual Classification”, 2016-09-01 ( ; similar)
“Towards an Integration of Deep Learning and Neuroscience”, Et Al 2016
“Towards an integration of deep learning and neuroscience”, 2016-08-22 ( ; similar)
“Improving Sentence Compression by Learning to Predict Gaze”, Et Al 2016
“Improving sentence compression by learning to predict gaze”, 2016-04-12 ( )
Wikipedia
Miscellaneous
-
https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhx268/4560155
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https://proceedings.neurips.cc/paper/2017/hash/d5e2c0adad503c91f91df240d0cd4e49-Abstract.html
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https://www.cs.cmu.edu/%7Eafyshe/papers/acl2014/jnnse_acl2014.pdf
-
https://www.lesswrong.com/posts/amK9EqxALJXyd9Rb2/paths-to-high-level-machine-intelligence
-
https://www.wired.com/story/the-long-search-for-a-computer-that-speaks-your-mind/
-
https://www.wired.com/story/tracking-readers-eye-movements-can-help-computers-learn/
Link Bibliography
-
https://www.nature.com/articles/s42003-022-03036-1
: “Brains and Algorithms Partially Converge in Natural Language Processing”, Charlotte Caucheteux, Jean-Rémi King: