Research Methods Courses

International Centre for Theoretical Sciences

A Glimpse into the Fun World of Probabilistic Methods by Moumanti Podder

Explore the fascinating realm of probabilistic methods, uncovering their applications and significance in various fields of mathematics and beyond.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Steve Brunton

Overview of Deep Reinforcement Learning Methods

Comprehensive exploration of deep reinforcement learning techniques, including Q-learning, actor-critic methods, policy networks, and gradient optimization for advanced AI decision-making and control systems.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Physics with Elliot

Methods for Differential Equations Physics Students Need to Know

Explore five powerful methods for solving differential equations in physics: ansatz, energy conservation, series expansion, Laplace transform, and Hamiltonian flow, with practical applications to harmonic oscillators.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Bolei Zhou

Towards Falsifiable Interpretability Research in Machine Learning - Lecture

Explore techniques for falsifiable interpretability in machine learning, focusing on saliency, individual neurons, and populations. Learn to build stronger hypotheses for more robust research.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

Simons Institute

Kernel Methods for Causal Inference

Explore kernel ridge regression for causal inference, covering dose responses, treatment effects, and extensions to various settings. Learn about consistency, efficiency, and robustness in estimation.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Simons Institute

Berkeley in the 80s - Andrew Yao's Turing Award-Winning Research

Explore Andrew Yao's groundbreaking research at Berkeley, his journey in theoretical computer science, and insights for aspiring researchers in this engaging interview.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Simons Institute

How to Fail Interpretability Research

Explore common pitfalls in AI interpretability research, including misconceptions about user trust, model understanding, and evaluation methods.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Simons Institute

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

Explore policy gradient methods in Markov Decision Processes, covering optimality, approximation, and key concepts like entropy regularization and natural policy gradient.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

Simons Institute

Faster Algorithms and New Iterative Methods for Computing the Stationary Distribution

Explore advanced algorithms and iterative methods for computing stationary distributions, with applications in optimization and graph theory.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Simons Institute

Interior Point Methods

Explore advanced interior point methods for optimization, covering key ideas, path following analysis, and specialized algorithms like Renegar's and regularized John ellipse barrier.

• YouTube
• 1 hour 8 minutes
• Self-Paced
• Free Video

Simons Institute

Stochastic Variance Reduction Methods for Policy Evaluation

Explore stochastic variance reduction methods for policy evaluation in reinforcement learning, covering MSPBE, SVRG, and SAGA algorithms with experimental results.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

MITCBMM

Neuroscience Methods Tutorial

Explore diverse neuroscience methods including psychophysics, electrophysiology, and signal analysis. Learn about electrode types, spike sorting, and oscillatory activity.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

MITCBMM

Nancy Kanwisher: History of Neuroimaging Research on Face Recognition

Explore the evolution of neuroimaging research on face recognition, from early studies to modern fMRI techniques, and discover key findings in this fascinating field of cognitive neuroscience.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Graham Neubig

Advanced NLP: Adversarial Methods for Text

Explore advanced NLP techniques including adversarial networks, discrete outputs, and input manipulation for robust language models and applications.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Databricks

MLflow Model Serving - Methods and Best Practices

Explore MLflow model serving techniques, including batch and real-time scoring, open-source and Databricks-managed options, with emphasis on new production-ready model serving features.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video