James Zou: "Deep learning for genomics: Introduction and examples"

Xiaoquan (William) Wen: "Bayesian approaches to integrative genetic association analysis..."

Nathan Wiebe - Quantum Machine Learning - IPAM at UCLA

Welcome and Keynote Session: What are the opportunities and challenges for ML in genomics research?

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4 Hours Chopin for Studying, Concentration & Relaxation

An Introduction to Graph Neural Networks: Models and Applications

Dana Pe'er: "Having fun with single-cell RNA-seq: imputation and manifolds"

Tom Griffiths - Understanding human intelligence through human limitations - IPAM at UCLA

Bossa Nova Jazz - Best Bossa Nova Covers 2025 for a Relaxing Vibe

MIT Deep Learning Genomics - Lecture 6 - Regulatory Genomics (Spring 2020)

Happy December Morning Jazz ☕ Positive Coffee Music and Delicate Bossa Nova Piano for Joyful Moods

Joshua Speagle - A Brief Introduction to Nested Sampling - IPAM at UCLA

Genomics, Imaging and AI - Ewan Birney

Machine Learning Zero to Hero (Google I/O'19)

Session 1: Algorithm development and machine learning approaches in genomics

Erik Winfree - Equilibrium is inference: lessons from a model of liquid-liquid phase separation

TAMEST 2024: AI for Genomics

Jennifer Listgarten: CRISPR Bioinformatics - Machine learning predictive models for guide design

Q2B24 Silicon Valley | Scott Aaronson, California Institute of Technology

Confirmatory Factor Analysis in R with lavaan