Our news
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Generalization is the Achilles heel of AI
dec 18, 2024 Kempner All Hands Meeting Prof. Kreiman gave an All Hands meeting at the Kempner Institute for the Study of Artificial and Natural Intelligence at Harvard. The talk focused on the challenges of building AI algorithms that can generalize to novel data and situations. Read more about some of the research presented in…
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Kreiman lab presentations at NeurIPS 2024
dec 10-15, 2024 Neural Information Processing Systems 2024 Several members of the Kreiman lab presented their cutting-edge research at NeurIPS 2024.
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Successes and challenges in computational models of vision
26Nov2024 Professor Kreiman gives a lecture at NUS National University of Singapore 6:30pm We now have powerful computer vision algorithms that can segment scenes, label objects, and recognize actions. It is tempting to use these algorithms as models of visual processing in biological brains. I will provide an overview of some of the successes in using neural network models to partially describe visual…
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Neuro 140/240 students named Rhodes Scholars for 2025
nov 17, 2024 Biological and artificial intelligence students named Rhodes Scholars Aneesh Muppidi and Ayush Noori, two students in the Neuro 140/240 Biological and Artificial Intelligence class, are among the 5 Harvard students awarded a Rhodes Scholarship for 2025. Read more about the announcement here.
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MCB80 Introduction to computational neuroscience
nov 5, 2024 Introduction to computational neuroscience Prof. Kreiman gives a lecture about the need for models in neuroscience to quantitatively analyze rich datasets, build theories of brain function, and advance artificial intelligence algorithms. Read more about recent research in the Kreiman lab here. Follow @gkreiman
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Theta phase precession in human episodic memory
oct 21, 2024 Human study provides evidence that theta phase precession supports memory formation and retrieval Medical xPress News article by Ingrid Fadelli
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Congratulations to Spandan Madan on his NeuroAI 2024 work!
10/10/2024 Improving out-of-distribution generalization by mimicking the human visual diet Spandan’s paper was accepted at NeuroAI @ NeurIPS 2024 In this work Spandan shows that a careful account of the visual input statistics that humans encounter during learning can help improve machine learning algorithms.
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Jie Zheng presents her work in a nanosymposium at SFN
october 5, 2024 Prefrontal and medial temporal neurons encode ordinal information of event seuences in humans Society for Neuroscience Annual Meeting. Nanosymposium NANO06.11. 3:30PM – 3:45PM
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Kreiman lab posters at SFN 2024
october 5 — OCTOBER 9, 2024 Presentations by the Kreiman lab at the Society for Neuroscience Annual Meeting 2024 Oct 5 2024. 3:30-3:45 Prefrontal and Medial Temporal Neurons Encode Ordinal Information of Event Sequences in Humans. Presented by Jie Zheng. Oct 7 2024, 8:00-13:00 Syntactic-feature encoding of language in the human brain. Presented by Pranav…