Gabriel Kreiman

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 58

Top Topics

Unsupervised Learning

Top Venues

Publications

Chenguang Li, Gabriel Kreiman, Sharad Ramanathan
Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks. Nat. Mac. Intell. 6 (6) (2024)
Spandan Madan, Will Xiao, Mingran Cao, Hanspeter Pfister, Margaret S. Livingstone, Gabriel Kreiman
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex. CoRR (2024)
Ravi Francesco Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization. ICLR (2024)
Vighnesh Subramaniam, Colin Conwell, Christopher Wang, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu
Revealing Vision-Language Integration in the Brain with Multimodal Networks. CoRR (2024)
Serena Bono, Spandan Madan, Ishaan Grover, Mao Yasueda, Cynthia Breazeal, Hanspeter Pfister, Gabriel Kreiman
Look Around! Unexpected gains from training on environments in the vicinity of the target. CoRR (2024)
Veedant Jain, Felipe dos Santos Alves Feitosa, Gabriel Kreiman
Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor. CoRR (2024)
Ravi Francesco Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization. CoRR (2023)
Trenton Bricken, Xander Davies, Deepak Singh, Dmitry Krotov, Gabriel Kreiman
Sparse Distributed Memory is a Continual Learner. CoRR (2023)
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu
BrainBERT: Self-supervised representation learning for intracranial recordings. CoRR (2023)
Trenton Bricken, Xander Davies, Deepak Singh, Dmitry Krotov, Gabriel Kreiman
Sparse Distributed Memory is a Continual Learner. ICLR (2023)
Trenton Bricken, Rylan Schaeffer, Bruno A. Olshausen, Gabriel Kreiman
Emergence of Sparse Representations from Noise. ICML (2023)
Stephen Casper, Dylan Hadfield-Menell, Gabriel Kreiman
White-Box Adversarial Policies in Deep Reinforcement Learning. SafeAI@AAAI (2023)
Parantak Singh, You Li, Ankur Sikarwar, Weixian Lei, Difei Gao, Morgan B. Talbot, Ying Sun, Mike Zheng Shou, Gabriel Kreiman, Mengmi Zhang
Learning to Learn: How to Continuously Teach Humans and Machines. ICCV (2023)
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu
BrainBERT: Self-supervised representation learning for intracranial recordings. ICLR (2023)
Zhiwei Ding, Xuezhe Ren, Erwan David, Melissa Vo, Gabriel Kreiman, Mengmi Zhang
Efficient Zero-shot Visual Search via Target and Context-aware Transformer. CoRR (2022)
Giorgia Dellaferrera, Gabriel Kreiman
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. CoRR (2022)
Spandan Madan, Li You, Mengmi Zhang, Hanspeter Pfister, Gabriel Kreiman
What makes domain generalization hard? CoRR (2022)
Mengmi Zhang, Marcelo Armendáriz, Will Xiao, Olivia Rose, Katarina Bendtz, Margaret S. Livingstone, Carlos Ponce, Gabriel Kreiman
Look twice: A generalist computational model predicts return fixations across tasks and species. PLoS Comput. Biol. 18 (11) (2022)
Stephen Casper, Dylan Hadfield-Menell, Gabriel Kreiman
White-Box Adversarial Policies in Deep Reinforcement Learning. CoRR (2022)
Ankur Sikarwar, Gabriel Kreiman
On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering. CoRR (2022)
Stephen Casper, Max Nadeau, Dylan Hadfield-Menell, Gabriel Kreiman
Robust Feature-Level Adversaries are Interpretability Tools. NeurIPS (2022)
Mengmi Zhang, Giorgia Dellaferrera, Ankur Sikarwar, Marcelo Armendáriz, Noga Mudrik, Prachi Agrawal, Spandan Madan, Andrei Barbu, Haochen Yang, Tanishq Kumar, Meghna Sadwani, Stella Dellaferrera, Michele Pizzochero, Hanspeter Pfister, Gabriel Kreiman
Human or Machine? Turing Tests for Vision and Language. CoRR (2022)
Karst M. P. Hoogsteen, Sarit Szpiro, Gabriel Kreiman, Eli Peli
Beyond the Cane: Describing Urban Scenes to Blind People for Mobility Tasks. ACM Trans. Access. Comput. 15 (3) (2022)
Xiao Liu, Ankur Sikarwar, Joo Hwee Lim, Gabriel Kreiman, Zenglin Shi, Mengmi Zhang
Reason from Context with Self-supervised Learning. CoRR (2022)
Giorgia Dellaferrera, Gabriel Kreiman
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. ICML (2022)
Parantak Singh, You Li, Ankur Sikarwar, Weixian Lei, Daniel Gao, Morgan Bruce Talbot, Ying Sun, Mike Zheng Shou, Gabriel Kreiman, Mengmi Zhang
Learning to Learn: How to Continuously Teach Humans and Machines. CoRR (2022)
Stephen Casper, Max Nadeau, Gabriel Kreiman
One Thing to Fool them All: Generating Interpretable, Universal, and Physically-Realizable Adversarial Features. CoRR (2021)
Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman
When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. ICCV (2021)
Mengmi Zhang, Rohil Badkundri, Morgan B. Talbot, Gabriel Kreiman
Hypothesis-driven Stream Learning with Augmented Memory. CoRR (2021)
Guy Ben-Yosef, Gabriel Kreiman, Shimon Ullman
What can human minimal videos tell us about dynamic recognition models? CoRR (2021)
Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman
Frivolous Units: Wider Networks Are Not Really That Wide. AAAI (2021)
Shashi Kant Gupta, Mengmi Zhang, Chia-Chien Wu, Jeremy M. Wolfe, Gabriel Kreiman
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS (2021)
Shashi Kant Gupta, Mengmi Zhang, Chia-Chien Wu, Jeremy M. Wolfe, Gabriel Kreiman
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. CoRR (2021)
Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman
When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. CoRR (2021)
Mengmi Zhang, Will Xiao, Olivia Rose, Katarina Bendtz, Margaret S. Livingstone, Carlos Ponce, Gabriel Kreiman
Look Twice: A Computational Model of Return Fixations across Tasks and Species. CoRR (2021)
Li Yuan, Will Xiao, Gabriel Kreiman, Francis E. H. Tay, Jiashi Feng, Margaret S. Livingstone
Adversarial images for the primate brain. CoRR (2020)
Vincent Jacquot, Zhuofan Ying, Gabriel Kreiman
Can Deep Learning Recognize Subtle Human Activities? CoRR (2020)
Mengmi Zhang, Claire Tseng, Gabriel Kreiman
Putting Visual Object Recognition in Context. CVPR (2020)
Mengmi Zhang, Gabriel Kreiman
What am I Searching for: Zero-shot Target Identity Inference in Visual Search. CoRR (2020)
Will Xiao, Gabriel Kreiman
XDream: Finding preferred stimuli for visual neurons using generative networks and gradient-free optimization. PLoS Comput. Biol. 16 (6) (2020)
William Lotter, Gabriel Kreiman, David D. Cox
A neural network trained for prediction mimics diverse features of biological neurons and perception. Nat. Mach. Intell. 2 (4) (2020)
Vincent Jacquot, Zhuofan Ying, Gabriel Kreiman
Can Deep Learning Recognize Subtle Human Activities? CVPR (2020)
Mengmi Zhang, Claire Tseng, Gabriel Kreiman
Putting visual object recognition in context. CoRR (2019)
Mengmi Zhang, Jiashi Feng, Karla Montejo, Joseph Kwon, Joo Hwee Lim, Gabriel Kreiman
Lift-the-Flap: Context Reasoning Using Object-Centered Graphs. CoRR (2019)
Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman
Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks. CoRR (2019)
Will Xiao, Gabriel Kreiman
Gradient-free activation maximization for identifying effective stimuli. CoRR (2019)
Kevin Wu, Eric Wu, Gabriel Kreiman
Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition. CoRR (2018)
Anil Palepu, Christine Sharmini Premanathan, Feraz Azhar, Martina Vendrame, Tobias Loddenkemper, Claus Reinsberger, Gabriel Kreiman, Kimberly A. Parkerson, Sridevi V. Sarma, William S. Anderson
Automating Interictal Spike Detection: Revisiting A Simple Threshold Rule. EMBC (2018)
William Lotter, Gabriel Kreiman, David D. Cox
A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. CoRR (2018)
Kevin Wu, Eric Wu, Gabriel Kreiman
Learning scene gist with convolutional neural networks to improve object recognition. CISS (2018)
Leyla Isik, Jedediah Singer, Joseph R. Madsen, Nancy Kanwisher, Gabriel Kreiman
What is changing when: Decoding visual information in movies from human intracranial recordings. NeuroImage 180 (Part) (2018)
Mengmi Zhang, Jiashi Feng, Keng Teck Ma, Joo Hwee Lim, Qi Zhao, Gabriel Kreiman
Finding any Waldo: zero-shot invariant and efficient visual search. CoRR (2018)
Mengmi Zhang, Jiashi Feng, Joo Hwee Lim, Qi Zhao, Gabriel Kreiman
What am I searching for? CoRR (2018)
Hanlin Tang, Bill Lotter, Martin Schrimpf, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David D. Cox, Gabriel Kreiman
Recurrent computations for visual pattern completion. CoRR (2017)
William Lotter, Gabriel Kreiman, David D. Cox
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. ICLR (Poster) (2017)
Nicholas Cheney, Martin Schrimpf, Gabriel Kreiman
On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations. CoRR (2017)
William Lotter, Gabriel Kreiman, David D. Cox
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. CoRR (2016)
Hanlin Tang, Jedediah Singer, Matias Ison, Gnel Pivazyan, Melissa Romaine, Elizabeth Meller, Victoria Perron, Marlise Arlellano, Gabriel Kreiman, Adriana Boulin, Rosa Frias, James Carroll, Sarah Dowcett
A machine learning approach to predict episodic memory formation. CISS (2016)
William Lotter, Gabriel Kreiman, David D. Cox
Unsupervised Learning of Visual Structure using Predictive Generative Networks. CoRR (2015)
Rajamanickam Murugan, Gabriel Kreiman
Theory on the Coupled Stochastic Dynamics of Transcription and Splice-Site Recognition. PLoS Comput. Biol. 8 (11) (2012)
Kendra S. Burbank, Gabriel Kreiman
Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections. PLoS Comput. Biol. 8 (3) (2012)
Gabriel Kreiman
Decoding ensemble activity from neurophysiological recordings in the temporal cortex. EMBC (2011)
Gabriel Kreiman, John H. R. Maunsell
Nine Criteria for a Measure of Scientific Output. Frontiers Comput. Neurosci. 5 (2011)
Gabriel Kreiman
Biological object recognition. Scholarpedia 3 (6) (2008)