Generative AI for Designing Future Medicines - A Biological Revolution
Exploring the revolutionary potential of Generative AI in biology, from designing new medicines to transforming human health and sustainability. Insights from a pioneering entrepreneur in biotech innovation.
AI in Cancer Detection and Treatment
Explore AI applications in cancer detection and treatment, covering advanced techniques for early diagnosis, personalized therapies, and improved patient outcomes.
Open Challenges in AI for Molecular Design: Representation, Experimental Alignment, and Oracle Reliability
Explore AI challenges in molecular design: representation, experimental alignment, and oracle reliance. Learn about new workflows and approaches to address real-world complexities in molecular discovery.
Illuminating Protein Space with Generative Models
Explore generative modeling for protein design, focusing on building learning systems that can generalize, scale, and create fit-for-purpose protein complexes on demand.
Promise and Perils of Artificial Intelligence in Healthcare
Explore AI's transformative impact on healthcare, from disease detection to personalized treatments, while examining ethical concerns and the irreplaceable human touch in patient care.
AI and Machine Learning in Drug Discovery and Development
Explore AI's revolutionary impact on drug discovery and healthcare with Daphne Koller. Gain insights into machine learning applications in biology, protein folding, and interdisciplinary collaboration for future medical breakthroughs.
Strategies for Integrating Deep Learning with Current Biomedical Research
Explore strategies for integrating deep learning in biomedical research, focusing on automated identification of clinical features from medical imaging and prediction of disease progression.
Phenomics in Drug Discovery: Microscopy and Machine Learning - Day 4
Explore phenomics in drug discovery through microscopy and machine learning techniques with expert Anne Carpenter.
Binding Affinity Prediction with Machine Learning-Based Docking - Lab 2
Explore ML-based docking techniques for predicting binding affinity in drug discovery, featuring insights from experts Stephan Thaler and Cristian Gabellini.
Applications of Deep Learning to Genomics and Digital Pathology
Explore deep learning applications in genomics and digital pathology, focusing on cutting-edge research and practical implementations in healthcare.
Exploring Molecular Space and Active Learning in Drug Discovery
Explore molecular space and active learning techniques for drug discovery with AI pioneer Yoshua Bengio's insights from the 2024 ML Summer School at Mila.
Lab 3 - De Novo Generation Explanation
Explore de novo molecule generation techniques with experts Emmanuel Bengio and Julien Roy in this recorded session from the 2024 Machine Learning for Drug Discovery Summer School.
Learning ML Interatomic Potentials - Day 2
Explore ML interatomic potentials for drug discovery with expert Gianni De Fabritiis. Gain insights into advanced techniques and applications in computational chemistry.
LLMs in Drug Discovery - Day 5
Explore the application of Large Language Models in drug discovery, focusing on innovative approaches and potential breakthroughs in pharmaceutical research.
Harnessing Geometric ML for Molecular Design - Day 3
Explore geometric machine learning techniques for innovative molecular design in drug discovery with expert Michael Bronstein.
Generative Models of Molecular Structures - Day 3
Explore generative models for molecular structures, focusing on applications in drug discovery and computational chemistry.
Machine Learning in Structure-Based Drug Discovery - Day 2
Explore machine learning applications in structure-based drug discovery, focusing on innovative techniques and their impact on pharmaceutical research.
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion
Explore Diffusion Forcing, a novel training paradigm combining next-token prediction and full-sequence diffusion for enhanced sequence generation and decision-making in AI applications.
Polaris - Industry-Led Initiative to Critically Assess ML for Real-World Drug Discovery
Explore an industry-led initiative critically assessing machine learning's impact on real-world drug discovery through the Polaris project.
Roughness of Molecular Property Landscapes and Its Impact on Modellability
Explore molecular property landscapes' roughness and its impact on modellability. Learn about the Roughness Index (ROGI) and its correlation with machine learning model performance in molecular discovery and drug design.
Introducing Bioptic - Machine Learning for Drug Discovery
Explore Bioptic's architecture, training, and scaling for machine learning in drug discovery with Vlad Vinograv.