Social And Emotional Learning Courses

Simons Institute

Representation Learning of Grounded Language and Knowledge - With and Without End-to-End Learning

Explore representation learning for grounded language and knowledge, covering end-to-end learning, procedural language challenges, and applications in cooking instructions and dialogue generation.

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

Simons Institute

Tractable Learning in Structured Probability Spaces

Explore tractable learning in structured probability spaces, focusing on logical circuits, probabilistic inference, and learning algorithms for complex datasets with constraints.

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

Simons Institute

Power of Active Sampling for Unsupervised Learning

Explore active sampling techniques for unsupervised learning, focusing on matrix completion, graphical models, and clustering. Learn about statistical tradeoffs and computational complexity.

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

Simons Institute

Machine Learning from Verbal User Instruction

Explore interactive machine learning through verbal instructions, focusing on sensor-effector systems and natural language processing for more intuitive human-AI interactions.

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

MITCBMM

Building a State Space for Song Learning

Explore how songbirds develop neural sequences for vocalizations, examining the role of auditory memory in shaping motor circuits and facilitating song learning through reinforcement mechanisms.

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

MITCBMM

Parallel Systems for Social and Spatial Reasoning Within the Brain's Apex Network

Explore parallel systems for social and spatial reasoning in the brain's apex network, examining cognitive architecture, neural mechanisms, and evolutionary origins through fMRI experiments and theoretical frameworks.

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

MITCBMM

Efficient Representation, Learning, and Planning Through Abstraction - Clustering Cognitive Spaces Into Submaps

Explore efficient representation and learning through abstraction, focusing on cognitive space clustering and its impact on memory, navigation, and planning in complex environments.

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

MITCBMM

Interpolation and Learning With Scale Dependent Kernels

Explore scale-dependent kernels in machine learning, covering overfitting, statistical theory, and practical applications in regression and interpolation.

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video

MITCBMM

Faces and Social Interactions

Explore primate social intelligence, face perception, and neural mechanisms behind facial recognition and social interactions.

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

MITCBMM

Learning What We Know and Knowing What We Learn - Gaussian Process Priors for Neural Data Analysis

Explore Gaussian process priors for neural data analysis, covering latent variable models, Bayesian inference, covariance kernels, and factor analysis. Gain insights into advanced techniques for understanding complex neural datasets.

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

MITCBMM

Social Visual Representations in Humans and Machines

Explore neural face representations, disentangled learning, and social interaction perception in vision, examining shared visual representations between humans and machines.

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

MITCBMM

DeepOnet - Learning Nonlinear Operators Based on the Universal Approximation Theorem of Operators

Learn to approximate nonlinear operators using DeepONet, a neural network architecture based on the universal approximation theorem. Explore applications in differential equations, fluid mechanics, and multiphysics problems.

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

MITCBMM

Beyond Empirical Risk Minimization - The Lessons of Deep Learning

Explore deep learning's challenge to traditional machine learning wisdom, examining the "double descent" risk curve and how over-parametrized models can generalize well despite perfect training fit.

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

MITCBMM

Machine Learning Accelerating Scientific Discovery

Explore how machine learning is revolutionizing scientific research, from consumer applications to breakthroughs in healthcare and video game development.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

MITCBMM

Neural Decoding of Spike Trains and Local Field Potentials with Machine Learning in Python

Learn Python-based machine learning techniques for neural decoding, focusing on preprocessing, model selection, and optimization for spike trains and local field potentials from macaque cortical areas.

• YouTube
• 1 hour 50 minutes
• Self-Paced
• Free Video