Valence Labs Courses

Scalable Emulation of Protein Equilibrium Ensembles with Generative Deep Learning

Explore groundbreaking deep learning techniques for generating protein structure ensembles, revealing conformational changes and thermodynamic properties for drug discovery applications.

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

Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains

Explore how scaling strategies can enhance Neural Network Interatomic Potentials (NNIPs), focusing on the Efficiently Scaled Attention Interatomic Potential (EScAIP) that achieves faster inference and better performance across chemical domains.

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

GENERator: A Long-Context Generative Genomic Foundation Model

Discover how GENERator, a generative genomic foundation model, decodes DNA sequences with a 98k base pair context length, demonstrating state-of-the-art performance in genomic research and biotechnological applications.

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

Single-cell Multiomics Data Integration and Generation with scPairing

Explore single-cell multiomics data integration with scPairing, a variational autoencoder model that embeds different cellular modalities into a common space, enabling generation of novel multiomics data without costly technologies.

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

Orb-v3: Atomistic Simulation at Scale

Explore Orb-v3, a next-generation universal interatomic potential that expands the performance-speed-memory frontier with 10x reduced latency and 8x reduced memory while maintaining near state-of-the-art accuracy for atomic simulations.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

Boltz-2 - Towards Accurate and Efficient Binding Affinity Prediction

Discover Boltz-2, a breakthrough AI model for predicting biomolecular structures and binding affinity with 1000x efficiency over traditional methods in drug discovery applications.

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

Action-Minimization Meets Generative Modeling - Efficient Transition Path Sampling

Explore how pre-trained generative models enable zero-shot transition path sampling in molecular systems using the Onsager-Machlup action functional for drug discovery.

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

Classifier-Free Guidance - From High-Dimensional Analysis to Generalized Guidance Forms

Explore high-dimensional analysis of Classifier-Free Guidance in diffusion models, revealing how dimensionality affects distribution accuracy and introducing robust non-linear guidance forms.

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

ATOMICA - Learning Universal Representations of Intermolecular Interactions

Discover how ATOMICA uses geometric deep learning to model intermolecular interactions across diverse biomolecular types, enabling disease pathway identification and dark proteome annotation.

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

FEAT: Free Energy Estimators with Adaptive Transport

Explore free energy estimation through the FEAT framework, which uses adaptive transport to provide consistent estimators and variational bounds, unifying equilibrium and non-equilibrium methods for neural free energy calculations.

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

Mapping Cells Through Time and Space with Moscot

Explore the moscot framework for single-cell genomics, enabling multimodal analysis across temporal and spatial dimensions to reconstruct developmental trajectories and uncover spatiotemporal dynamics in biological systems.

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

Identifying Perturbation Targets Through Causal Differential Networks

Discover how to identify biological intervention targets using causal differential networks for drug discovery and cell engineering applications.

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

Meta Flow Matching - Integrating Vector Fields on the Wasserstein Manifold

Explore advanced flow-based modeling techniques for predicting biological system dynamics, focusing on population-level evolution and personalized medicine applications using Graph Neural Networks.

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

Neural Entropy - Understanding Deep Learning Through Information Theory and Diffusion Models

Explore the intersection of deep learning and information theory through diffusion models, examining how neural networks store and process information using principles from thermodynamics and optimal transport.

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

scPRINT - Pre-training on 50 Million Cells for Robust Gene Network Predictions

Discover how scPRINT, a large cell model pre-trained on 50M+ cells, revolutionizes gene network inference while offering powerful capabilities in denoising, batch correction, and cell prediction.

• YouTube
• 1 hour 12 minutes
• Self-Paced
• Free Video