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Title: Correlated Dirac and Weyl Semimetals Abstract: We study the resistivity of three-dimensional semimetals with linear dispersion in the presence of on-site electron-electron interaction. The …

The scope of NMC4 includes computational neuroscience and machine learning work that has a biological link. The event will include a combination of virtual and in-person conference …

Topic: Cluster of Excellence Physics of Life Abstract: One of the most remarkable examples of self-organized structure formation is the development of a complex organism from a …

All lectures in this series will be held 10-11:15am US EDT and are open to all interested scientists. For further information please contact Dr. Igor Tupitsyn …

Two days of talks, keynote lectures and discussion panels at the crossroads of biological and artificial intelligence. Watch out also for the 2-day educational session on Nov …

Title: Tractability, generalization and overparametrization in linear and nonlinear models Abstract: Empirical risk minimization (ERM) is the dominant paradigm in statistical learning. Optimizing the empirical risk of neural …

Title: Preconditioners for linear systems

Please email [email protected] for Zoom information if you would like to participate. Title: The Millimeter Sky from the Atacama Cosmology Telescope Abstract: I will show maps …

… mirror symmetry, formulated by Kontsevich in 1994, naturally produces hosts of homological invariants. Sometimes, it can be made manifest, and then its striking mathematical power comes to …

Quantum invariants of knots (also known as Chern-Simons knot invariants) have many applications in mathematics and physics. For example, Khovanov showed in 1999 that the simplest such …

The group will focus on studying *hormone circuits*, which impact so much of human biology, disease (e.g. diabetes, depression) and behavior. No background is needed. The overall …

Title: Hamiltonian Estimations by Inverse Renormalisation Group and Convolution Nets Abstract: Estimating high-dimensional probability distributions and physical Hamiltonians from data is an old outstanding problem. It is …

Title: How flies make and use their appendages Abstract: My plan is to present an overview of the current efforts in my lab, providing necessary background when needed …

All lectures in this series will be held 10-11:15am US EDT and are open to all interested scientists. For further information please contact Dr. Igor Tupitsyn …

Speaker: Paul Kim, Software Engineer, Simons Machine Learning Center Title: Learning to automate Cryo-EM data collection with Ptolemy Abstract: Over the past decade, cryogenic electron microscopy (cryo …

SfN's 50th annual meeting is the premier venue for neuroscientists to present emerging science, learn from experts, forge collaborations with peers, explore new tools and technologies, and …

Discussion Lead: Lester Mackey, Microsoft Research/Stanford University Topic: Kernel and Stein thinning for MCMC Link: TBD

… holes provide a window into quantum gravity and how scientists use the ‘bootstrap’ technique to study them. This line of research leads from black hole thermodynamics to …

Black holes have mysterious properties that indicate that they are composed of an enormous number of microscopic parts. This has led to the idea that in quantum gravity …

Title: Embedding theories for quantum simulations on hybrid classical-quantum architectures Abstract: We discuss a recently developed quantum embedding theory [1] scalable to large systems, and its application …

Presenter: Dr. Elizabeth R. Gavin, Ph.D., DamonB. Pfeiffer Professor of MolecularBiology Associated Faculty of the Princeton Neuroscience Institute Princeton University Topic: Looking to the future: assembly and …

Title: The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning Abstract: The success of deep learning is due, to a …

Please email [email protected] for Zoom information if you would like to participate.

Discussion Lead: Lee Devilin & Simon Maskell, Liverpool University Topic: Lee Devlin, Paul Horridge, Peter L. Green, Simon Maskell. 2021. The no-U-turn sampler as a proposal distribution …

Presenter: M. Cristina Marchetti, Ph.D., Professor, Physics University of California, Santa Barbara Topic: Interfacial properties of active fluids Abstract: There are many situations where active fluids coexist …

Recent advances in deep neural networks (DNNs), combined with open, easily-accessible implementations, have made DNNs a powerful, versatile method used widely in both machine learning and neuroscience …

Some events can impact the volatilities of most assets, asset classes, sectors and countries, causing severe damage to investment portfolios. The magnitude of such shocks is defined as …

Title: The Coming Revolution in Computational Astrophysics Abstract: Large-scale computer simulations are increasingly crucial in explaining astrophysical phenomena. Just one recent example is the stunning agreement of …

Title: Perturbational Complexity by Distribution Mismatch: A Systematic Analysis of Reinforcement Learning in Reproducing Kernel Hilbert Space Abstract: Most existing theoretical analysis of reinforcement learning (RL) is limited …

Presenter: Professor Raymond E. Goldstein FRS Schlumberger Professor of Complex Physical Systems Department of Applied Mathematics and Theoretical Physics Centre for Mathematical SciencesUniversity of Cambridge Topic: Cytoplasmic Streaming …

All lectures in this series will be held 10-11:15am US EDT and are open to all interested scientists. For further information please contact Dr. Igor Tupitsyn …

Discussion Lead: Charles Margossian, Columbia University Topic: Nested Rhat: Assessing Convergence for Markov chains Monte Carlo when using many short chains Please email Cindy Rampersad at crampersad@flatironinstitute …

You’re invited to join two talks on Friday, October 29th, 10 am – 12 pm. Both will be hybrid events, held in the 2nd floor auditorium (IDA) as …

Expander graphs have been useful in computer science with versatile applications, including coding theory, networking, computational complexity and geometry. High-dimensional expanders are a generalization that has been …

Title: A New Model for Interstellar Dust: “Astrodust” + PAHs Abstract: Observations strongly suggest that interstellar dust in the Milky Way consists predominantly of a single composite material, which …

Title: Surface State Magnetoresistance in 3D Topological Insulators Abstract: Topological insulators (TIs) have a variety of unique transport properties, including strong spin-orbit coupling and symmetry-protected spin …

… will not be granted without this documentation. On-site registration will not be permitted. Walk-in entry will be denied. October 27, 2021 Henry Yuen | Noncommutative Property …