Biological object recognition. - Gabriel Kreiman (Scholarpedia, 2008)

Decoding ensemble activity from neurophysiological recordings in the temporal cortex. - Gabriel Kreiman (EMBC, 2011)

Nine Criteria for a Measure of Scientific Output. - Gabriel Kreiman; John H. R. Maunsell (Frontiers Comput. Neurosci., 2011)

Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections. - Kendra S. Burbank; Gabriel Kreiman (PLoS Comput. Biol., 2012)

Theory on the Coupled Stochastic Dynamics of Transcription and Splice-Site Recognition. - Rajamanickam Murugan; Gabriel Kreiman (PLoS Comput. Biol., 2012)

Unsupervised Learning of Visual Structure using Predictive Generative Networks. - William Lotter; Gabriel Kreiman; David D. Cox (CoRR, 2015)

A machine learning approach to predict episodic memory formation. - Hanlin Tang; Jedediah Singer; Matias Ison; Gnel Pivazyan; Melissa Romaine; Elizabeth Meller; Victoria Perron; Marlise Arlellano; Gabriel Kreiman; Adriana Boulin; Rosa Frias; James Carroll; et al. (CISS, 2016)

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. - William Lotter; Gabriel Kreiman; David D. Cox (ICLR (Poster), 2017)

On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations. - Nicholas Cheney; Martin Schrimpf; Gabriel Kreiman (CoRR, 2017)

Recurrent computations for visual pattern completion. - Hanlin Tang; Bill Lotter; Martin Schrimpf; Ana Paredes; Josue Ortega Caro; Walter Hardesty; David D. Cox; Gabriel Kreiman (CoRR, 2017)

Learning scene gist with convolutional neural networks to improve object recognition. - Kevin Wu; Eric Wu; Gabriel Kreiman (CISS, 2018)

Automating Interictal Spike Detection: Revisiting A Simple Threshold Rule. - Anil Palepu; Christine Sharmini Premanathan; Feraz Azhar; Martina Vendrame; Tobias Loddenkemper; Claus Reinsberger; Gabriel Kreiman; Kimberly A. Parkerson; Sridevi V. Sarma; William S. Anderson (EMBC, 2018)

A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. - William Lotter; Gabriel Kreiman; David D. Cox (CoRR, 2018)

Finding any Waldo: zero-shot invariant and efficient visual search. - Mengmi Zhang; Jiashi Feng; Keng Teck Ma; Joo Hwee Lim; Qi Zhao 001; Gabriel Kreiman (CoRR, 2018)

What am I searching for? - Mengmi Zhang; Jiashi Feng; Joo Hwee Lim; Qi Zhao 001; Gabriel Kreiman (CoRR, 2018)

What is changing when: Decoding visual information in movies from human intracranial recordings. - Leyla Isik; Jedediah Singer; Joseph R. Madsen; Nancy Kanwisher; Gabriel Kreiman (NeuroImage, 2018)

Lift-the-Flap: Context Reasoning Using Object-Centered Graphs. - Mengmi Zhang; Jiashi Feng; Karla Montejo; Joseph Kwon; Joo Hwee Lim; Gabriel Kreiman (CoRR, 2019)

Gradient-free activation maximization for identifying effective stimuli. - Will Xiao; Gabriel Kreiman (CoRR, 2019)

Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks. - Stephen Casper; Xavier Boix; Vanessa D'Amario; Ling Guo; Martin Schrimpf; Kasper Vinken; Gabriel Kreiman (CoRR, 2019)

Can Deep Learning Recognize Subtle Human Activities? - Vincent Jacquot; Zhuofan Ying; Gabriel Kreiman (CVPR, 2020)

Putting Visual Object Recognition in Context. - Mengmi Zhang; Claire Tseng; Gabriel Kreiman (CVPR, 2020)

Adversarial images for the primate brain. - Li Yuan 007; Will Xiao; Gabriel Kreiman; Francis E. H. Tay; Jiashi Feng; Margaret S. Livingstone (CoRR, 2020)

A neural network trained for prediction mimics diverse features of biological neurons and perception. - William Lotter; Gabriel Kreiman; David D. Cox (Nat. Mach. Intell., 2020)

XDream: Finding preferred stimuli for visual neurons using generative networks and gradient-free optimization. - Will Xiao; Gabriel Kreiman (PLoS Comput. Biol., 2020)

Frivolous Units: Wider Networks Are Not Really That Wide. - Stephen Casper; Xavier Boix; Vanessa D'Amario; Ling Guo; Martin Schrimpf; Kasper Vinken; Gabriel Kreiman (AAAI, 2021)

When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. - Philipp Bomatter; Mengmi Zhang; Dimitar Karev; Spandan Madan; Claire Tseng; Gabriel Kreiman (ICCV, 2021)

Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. - Shashi Kant Gupta; Mengmi Zhang; Chia-Chien Wu; Jeremy M. Wolfe; Gabriel Kreiman (NeurIPS, 2021)

Look Twice: A Computational Model of Return Fixations across Tasks and Species. - Mengmi Zhang; Will Xiao; Olivia Rose; Katarina Bendtz; Margaret S. Livingstone; Carlos R. Ponce; Gabriel Kreiman (CoRR, 2021)

Hypothesis-driven Stream Learning with Augmented Memory. - Mengmi Zhang; Rohil Badkundri; Morgan B. Talbot; Gabriel Kreiman (CoRR, 2021)

What can human minimal videos tell us about dynamic recognition models? - Guy Ben-Yosef; Gabriel Kreiman; Shimon Ullman (CoRR, 2021)

One Thing to Fool them All: Generating Interpretable, Universal, and Physically-Realizable Adversarial Features. - Stephen Casper; Max Nadeau; Gabriel Kreiman (CoRR, 2021)

Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. - Giorgia Dellaferrera; Gabriel Kreiman (ICML, 2022)

Robust Feature-Level Adversaries are Interpretability Tools. - Stephen Casper; Max Nadeau; Dylan Hadfield-Menell; Gabriel Kreiman (NeurIPS, 2022)

On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering. - Ankur Sikarwar; Gabriel Kreiman (CoRR, 2022)

What makes domain generalization hard? - Spandan Madan; Li You; Mengmi Zhang; Hanspeter Pfister; Gabriel Kreiman (CoRR, 2022)

Reason from Context with Self-supervised Learning. - Xiao Liu; Ankur Sikarwar; Joo Hwee Lim; Gabriel Kreiman; Zenglin Shi; Mengmi Zhang (CoRR, 2022)

Human or Machine? Turing Tests for Vision and Language. - Mengmi Zhang; Giorgia Dellaferrera; Ankur Sikarwar; Marcelo Armendáriz; Noga Mudrik; Prachi Agrawal; Spandan Madan; Andrei Barbu; Haochen Yang; Tanishq Kumar; Meghna Sadwani; Stella Dellaferrera; et al. (CoRR, 2022)

Efficient Zero-shot Visual Search via Target and Context-aware Transformer. - Zhiwei Ding; Xuezhe Ren; Erwan J. David; Melissa Le-Hoa Vo; Gabriel Kreiman; Mengmi Zhang (CoRR, 2022)

Learning to Learn: How to Continuously Teach Humans and Machines. - Parantak Singh; You Li; Ankur Sikarwar; Weixian Lei; Daniel Gao; Morgan Bruce Talbot; Ying Sun 001; Mike Zheng Shou; Gabriel Kreiman; Mengmi Zhang (CoRR, 2022)

Beyond the Cane: Describing Urban Scenes to Blind People for Mobility Tasks. - Karst M. P. Hoogsteen; Sarit Szpiro; Gabriel Kreiman; Eli Peli (ACM Trans. Access. Comput., 2022)

Look twice: A generalist computational model predicts return fixations across tasks and species. - Mengmi Zhang; Marcelo Armendáriz; Will Xiao; Olivia Rose; Katarina Bendtz; Margaret S. Livingstone; Carlos R. Ponce; Gabriel Kreiman (PLoS Comput. Biol., 2022)

White-Box Adversarial Policies in Deep Reinforcement Learning. - Stephen Casper; Dylan Hadfield-Menell; Gabriel Kreiman (SafeAI@AAAI, 2023)

Learning to Learn: How to Continuously Teach Humans and Machines. - Parantak Singh; You Li; Ankur Sikarwar; Weixian Lei; Difei Gao; Morgan B. Talbot; Ying Sun 001; Mike Zheng Shou; Gabriel Kreiman; Mengmi Zhang (ICCV, 2023)

Sparse Distributed Memory is a Continual Learner. - Trenton Bricken; Xander Davies; Deepak Singh; Dmitry Krotov; Gabriel Kreiman (ICLR, 2023)

BrainBERT: Self-supervised representation learning for intracranial recordings. - Christopher Wang; Vighnesh Subramaniam; Adam Uri Yaari; Gabriel Kreiman; Boris Katz; Ignacio Cases; Andrei Barbu (ICLR, 2023)

Emergence of Sparse Representations from Noise. - Trenton Bricken; Rylan Schaeffer; Bruno A. Olshausen; Gabriel Kreiman (ICML, 2023)

Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization. - Ravi Francesco Srinivasan; Francesca Mignacco; Martino Sorbaro 001; Maria Refinetti; Avi Cooper; Gabriel Kreiman; Giorgia Dellaferrera (ICLR, 2024)

Revealing Vision-Language Integration in the Brain with Multimodal Networks. - Vighnesh Subramaniam; Colin Conwell; Christopher Wang; Gabriel Kreiman; Boris Katz; Ignacio Cases; Andrei Barbu (ICML, 2024)

Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex. - Spandan Madan; Will Xiao; Mingran Cao; Hanspeter Pfister; Margaret S. Livingstone; Gabriel Kreiman (NeurIPS, 2024)

Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli. - Christopher Wang; Adam Uri Yaari; Aaditya Singh; Vighnesh Subramaniam; Dana Rosenfarb; Jan DeWitt; Pranav Misra; Joseph R. Madsen; Scellig S. Stone; Gabriel Kreiman; Boris Katz; Ignacio Cases; et al. (NeurIPS, 2024)

Look Around! Unexpected gains from training on environments in the vicinity of the target. - Serena Bono; Spandan Madan; Ishaan Grover; Mao Yasueda; Cynthia Breazeal; Hanspeter Pfister; Gabriel Kreiman (CoRR, 2024)

Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor. - Veedant Jain; Felipe dos Santos Alves Feitosa; Gabriel Kreiman (CoRR, 2024)

L-WISE: Boosting Human Image Category Learning Through Model-Based Image Selection And Enhancement. - Morgan B. Talbot; Gabriel Kreiman; James J. DiCarlo; Guy Gaziv (CoRR, 2024)

Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks. - Chenguang Li; Gabriel Kreiman; Sharad Ramanathan (Nat. Mac. Intell., 2024)

Cogitate-consortium/cogitate-experiment-code: v1.0. - Cogitate Consortium; Oscar Ferrante; Urszula Gorska; Rony Hirschhorn; Aya Khalaf; Alex Lepauvre; Ling Liu; David Richter 003; Katarina Bendtz; David Mazumder; Hao Zhou; Hal Blumenfeld; et al. (Zenodo, 2024)

The Indoor-Training Effect: Unexpected Gains from Distribution Shifts in the Transition Function. - Serena Bono; Spandan Madan; Ishaan Grover; Mao Yasueda; Cynthia Breazeal; Hanspeter Pfister; Gabriel Kreiman (AAAI, 2025)

L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement. - Morgan Bruce Talbot; Gabriel Kreiman; James J. DiCarlo; Guy Gaziv (ICLR, 2025)

Unraveling the geometry of visual relational reasoning. - Jiaqi Shang; Gabriel Kreiman; Haim Sompolinsky (CoRR, 2025)

Tuned Compositional Feature Replays for Efficient Stream Learning. - Morgan B. Talbot; Rushikesh Zawar; Rohil Badkundri; Mengmi Zhang; Gabriel Kreiman (IEEE Trans. Neural Networks Learn. Syst., 2025)

Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance. - Lorenzo Tausani; Paolo Muratore; Morgan B. Talbot; Giacomo Amerio; Gabriel Kreiman; Davide Zoccolan (CoRR, 2025)