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DateActivityNameTitleVideo
Available
Slides
Available
2024-03-27nsbp_iss
Jones, Ilenna (Kempner Institute at Harvard)
Quantifying the impact of dendritic properties on neuronal computation.YesYes
2023-12-11pti23Tutorial on Feynman diagram methods for neural network correlatorsYesNo
2023-12-08deeplearning23
Atanasov, Alex (Harvard)
Tutorial on Neural Scaling LawsYesNo
2023-11-29friends
Chklovskii, Dmitri "Mitya" (Flatiron Institute)
Can Neuroscience Help Advance Artificial Intelligence?YesNo
2023-11-22deeplearning23
Simon, Jamie (UC Berkeley)
Tutorial on "kernel/lazy" vs "rich/feature-learning" regimes in wide netsYesNo
2023-11-20bblunch
Sompolinsky, Haim (Hebrew Univ.)
Statistical Mechanics of Deep LearningYesNo
2023-11-17deeplearning23
Yaida, Sho (META)
Tutorial on Transformers with IndicesYesYes
2023-07-21brainlearn23
Wolpert, Daniel (Columbia University)
Keynote: Statistical learning in sensorimotor controlYesNo
2023-07-06brainlearn23
Linden, Jennifer (University College London)
Introduction to the session and Representation of Primitives for Statistical Learning in the Auditory SystemYesNo
2023-07-03brainlearn23Participant's one slide-introductions: part 6YesNo
2023-07-03brainlearn23
Hoz, Livia de (Charite Berlin)
Fiser, Jozsef (Central European University)
General introduction, information session, practicalitiesYesNo
2023-06-21brainlearn23
Mattar, Marcelo (New York University)
Related Words: modes
Review talkYesYes
2023-06-20brainlearn23Participant's one slide-introductions: part 5YesNo
2023-06-16brainlearn23
Turk-Browne, Nick (Yale University)
Related Words: learning, memory
Review: What is the relationship between statistical learning and episodic memory?YesNo
2023-06-15brainlearn23
Hoz, Livia de (Charite)
Akrami, Athena (Sainsbury Wellcome Centre)
Related Words: discussion, learning
Introduction to the neurobiology and systems neuroscience view of statistical learningYesNo
2023-06-15brainlearn23Participant's one slide-introductions: part 4YesNo
2023-06-14brainlearn23Participant's one slide-introductions: part 3YesNo
2023-06-13brainlearn23Participant's one slide-introductions: part 1YesNo
2023-06-13brainlearn23Participant's one slide-introductions: part 2YesNo
2023-06-13brainlearn23
Hoz, Livia de (Charite)
Fiser, Jozsef (Central European University)
Lengyel, Mate (University of Cambridge)
Related Words: learning
General introduction, information session, practicalitiesYesNo
2023-03-15galevo23
Walmsley, Mike (University of Manchester)
Review talk on combining the power of citizen science and machine learningYesNo
2023-03-09bblunchLearning from billions of galaxies: Can our understanding of galaxy formation keep up with the upcoming data revolution?YesNo
2023-02-23galevo23
Sotoudeh, Hadi (University of Montreal)
Tutorial on Probabilistic U-NetsYesNo
2023-02-15galevo23
Hearin, Andrew (Argonne National Laboratory)
Tutorial on differential programming with JAXYesNo
2023-02-08galevo23
Malz, Alex (New York University)
Tutorial on photo-z's and uncertaintiesYesNo
2023-01-25galevo23
Behroozi, Peter (University of Arizona)
Tutorial: Galaxy scaling relations through working with Universe MachineYesNo
2023-01-24galevo23
Santi, Natali de (Flatiron Institute/University of Sao Paulo)
Lovell, Chris (University of Portsmouth)
Tutorial: The galaxy-halo connection and Machine Learning approachesYesNo
2023-01-19galevo23
Wu, John (STScI)
Tutorial: Introduction to Convolutional Neural NetworksYesNo
2023-01-18galevo23 Tutorial: Large-scale galaxy formation simulations and Machine Learning approachesYesNo
2023-01-17galevo23 Introducing the program: Galaxy evolution and data-driven advancesYesYes
2023-01-17galevo23
Starkenburg, Tjitske (Northwestern University)
Related Words: galaxy
Wu, John (STScI)
Behroozi, Peter (University of Arizona)
Villaescusa-Navarro, Francisco (Flatiron Institute)
Welcome and Introduction to the virtual programYesNo
2019-03-21machine19 Discussion: Introduction to kernel methods for machine learningYesNo
2019-03-13machine19
Rocchetto, Andrea (Oxford/UCL)
Tutorial: Overview of classical and quantum learning theoryYesNo
2019-03-06machine19
Chen, Jing (Flatiron)
Tutorial: Tensor networks and RBMsYesYes
2019-02-25bblunch
Carleo, Giuseppe (Flatiron Institute)
Dreaming, computing, inspiring: Flavors of machine learning in many-body quantum physicsYesNo
2019-02-21machine19
Inack, Estelle (Perimeter)
Tutorial: Variational Monte Carlo and Machine LearningYesNo
2019-02-16machinet_c19
Bahri, Yasaman (Google)
Related Words: deep
Introduction to Deep LearningYesYes
2019-02-16machinet_c19WelcomeYesNo
2019-02-16machinet_c19How machine learning is revolutionizing drug discovery and material design: Improving electronic structure calculationsYesYes
2019-02-16machinet_c19
Fournier, Justin (Cypress High School)
Gross, David (KITP)
Related Words: kitp, physics, string, theory, welcome
STEP UP 4 WomenYesYes
2019-02-16machinet_c19
Sierens, Lauren Hayward (Perimeter Inst.)
Understanding how neural networks understandYesYes
2019-02-16machinet_c19
Hezaveh, Yashar (Flatiron Institute)
Related Words: mapping
Mapping distant galaxies with artificial intelligenceYesNo
2019-02-16machinet_c19
Torlai, Giacomo (Flatiron Institute)
Quantum physics of many particles: a data-driven perspectiveYesNo
2019-02-06machine19
Sels, Dries (Harvard)
Tutorial: Reinforcement Learning for PhysicistsYesNo
2019-01-30machine19
Albergo, Michael (Perimeter Institute)
Tutorial: An Overview of Recent Generative ModelsYesNo
2019-01-30scape19
Mezard, Marc (École Normale Supérieure Paris)
Mezard, Marc (ENS Paris)
Artificial intelligence: success, limits, myths and threats [Podcast][Aud][Cam] KITP Public LectureYesNo
2019-01-28scape19The many facets of the rough high-dimensional landscape problem[Podcast][Aud][Cam] KITP Blackboard LunchYesNo
2019-01-24scape19An overview of empirical studies in neural networksYesYes
2019-01-22scape19Selected review of 30 years of physics research on artificial neural networksYesNo
2019-01-11scape_c19TUTORIAL Sum-of-Squares, with a View Towards Average-case ComplexityYesYes
2019-01-10scape_c19
Cugliandolo, Leticia (Sorbonne Universités)
Related Words: dynamics, glassy, quantum, systems
TUTORIAL: Dynamics in High Dimensional LandscapesYesYes
2019-01-09scape_c19
Srebro, Nathan (Chicago)
TUTORIAL: Optimization Methods from a Machine Learning PerspectiveYesNo
2019-01-08scape_c19
Mezard, Marc (ENS-Paris)
TUTORIAL: Disordered systems in Physics, Information Theory and Computer ScienceYesYes
2019-01-07scape_c19TUTORIAL: Generalization and Overfitting -- Basic Concepts and Open QuestionsYesYes