
Explore Julia's advantages for data science, including speed, economic viability, and reduced carbon footprint compared to R and Python.

Explore Physics-Informed Neural Networks (PINNs) and their application in solving inverse problems in scientific computing and engineering.

Explore the fascinating world of frustrated bearings, their unique properties, and applications in physics and engineering. Discover how these systems exhibit novel states and unexpected behaviors in 2D and 3D.

Explore non-equilibrium theory for non-ergodic systems using time-and-space averaging, focusing on internal energy dynamics and applications to immiscible fluid flow in porous media.

Explore fluid-fluid interface dynamics on heterogeneous surfaces, from stick-slip to steady sliding. Uncover key parameters and timescales in partial wetting displacement through coupled differential equations and mechanical analogies.

Explore continuous upscaling methods for multi-scale modeling. Learn about gradual smoothing transformations, upscaling rules for various physical quantities, and applications to steady-state diffusion problems.

Explore the amplituhedron's geometric properties, connections to various mathematical fields, and recent progress on key conjectures in this advanced mathematical lecture.

Explore scan statistics for detecting anomalies in random fields, focusing on applications in spatio-temporal data analysis and high-dimensional forecasting methods.

Explore mixing properties of (non-)stationary INGARCH(1,1) processes in this mathematical conference talk, focusing on adaptive and high-dimensional spatio-temporal forecasting methods.

Explore Lyapunov exponents in Navier-Stokes equations through Alex Blumenthal's conference talk, delving into probabilistic techniques for random and time-dependent dynamical systems.

Explore non-convex SGD and Lojasiewicz-type conditions for deep learning in this mathematical conference talk by Kevin Scaman at CIRM.

Explore clustering with tangles, covering partitions, agreement parameters, cost functions, and applications in machine learning and signal processing on graphs.

Explore statistical methods for comparing spatio-temporal networks, focusing on brain analysis and graph comparisons. Learn nodal statistics and structural patterns for network characterization.

Explore combinatorial Reid's recipe for consistent dimer models, focusing on Makai correspondence, modular spaces, and derived interpretations in algebraic geometry.

Explore regularity of vortex and SQG patches, covering existence, global irregularity, numerical simulations, and geometric analysis in fluid dynamics.

Explore projective Reed Muller codes with Sudhir Ghorpade, revisiting key concepts and recent developments in algebraic coding theory.

Explore capacity of Private Information Retrieval from coded and colluding servers. Gain insights into algebraic and combinatorial methods for coding and cryptography.

Explore APN and AB power functions in algebraic cryptography, focusing on their properties and applications in secure communication systems.

Explore innovative approaches to protein-protein interaction prediction by integrating global perspectives with sequence-based methods.

Explore metastability in mean-field-like spin systems with random couplings, focusing on Glauber dynamics and quantitative estimates in large volumes at fixed temperatures.

Explore ecological surprises, resilience, tipping points, and early-warning signals in complex systems. Gain insights into anticipating and understanding sudden environmental changes.