Slides

• Yang-Mills existence and mass gap.
• Neural networks can learn any low complexity pattern.
• Rigorous results for timelike Liouville field theory.
• Spectral gap for nonreversible Markov chains.
• Mass generation by the Higgs mechanism.
• Spin glass phase at zero temperature in the Edwards-Anderson model.
• An invariance principle for 1D KPZ.
• A new coefficient of correlation.
• Some progress on 3D Yang-Mills.
• Local KPZ behavior under arbitrary scaling limits.
• New results for surface growth.
• Yang-Mills on the lattice: New results and open problems.
• A probabilistic mechanism for quark confinement.
• Feature Ordering by Conditional Independence.
• Average Gromov hyperbolicity and the Parisi ansatz.
• Yang-Mills for mathematicians.
• Wilson loops in Ising lattice gauge theory.
• Infosys-ICTS Ramanujan Lectures (2019), Lecture 1.
• Infosys-ICTS Ramanujan Lectures (2019), Lecture 2.
• Infosys-ICTS Ramanujan Lectures (2019), Lecture 3.
• Some progress on 2D KPZ.
• An introduction to gauge theories for probabilists.
• Decay of correlations in the random field Ising model.
• Rigidity of the 3D hierarchical Coulomb gas.
• A general method for lower bounds on fluctuations of random variables.
• The endpoint distribution of directed polymers.
• The sample size required in importance sampling.
• The 1/N expansion for lattice gauge theories.
• The Yang-Mills free energy.
• Gauge-string duality in lattice gauge theories.
• A short survey of Stein's method. (ICM lecture)
• Least squares under convex constraint.
• Nonlinear large deviations.
• Matrix estimation by Universal Singular Value Thresholding.
• St. Petersburg School in Probability and Statistical Physics (2012), Lecture 1.
• St. Petersburg School in Probability and Statistical Physics (2012), Lecture 2.
• St. Petersburg School in Probability and Statistical Physics (2012), Lecture 3.
• Invariant measures and the soliton resolution conjecture.
• The universal relation between exponents in first-passage percolation.
• Superconcentration and related phenomena (Luminy lecture notes).
• Applications of dense graph limits in probability and statistics.
• Probabilistic methods for discrete nonlinear Schrödinger equations
• Random graphs with a given degree sequence.
• The large deviation principle for the Erdős-Rényi random graph.
• Random multiplicative functions in short intervals.
• The missing log in large deviations for triangle counts.
• Superconcentration.
• Tutorial lectures given at Stein's method conference in Singapore.
• Chaos, concentration, and multiple valleys.
• A new approach to strong embeddings.
• Spin glasses and Stein's method.
• Fluctuations of eigenvalues and second order Poincaré inequalities.
• Gravitational allocation to Poisson points.
• Convex polytopes, interacting particles, spin glasses, and finance.
• A new method of normal approximation.
• On the concentration of Haar measures.
• A generalization of the Lindeberg principle.
• Concentration inequalities with exchangeable pairs.