Geometric Deep Learning for Protein Understanding
Explore geometric deep learning techniques for protein analysis and understanding, focusing on advanced computational methods in molecular biology.
What's Really Going On in Machine Learning? Some Minimal Models - Stephen Wolfram Reading
Explore Stephen Wolfram's insights on machine learning through minimal models, covering neural nets, discrete rule arrays, and optimization processes. Gain a deeper understanding of ML fundamentals and their implications.
Computational Conversations - Do We Use the Maths We Learned in School? - Episode 8
Explore the relevance of school mathematics in computational careers through reflections on useful skills and modern perspectives from industry experts.
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
Explore equivariant energy-based models and Stein variational gradient descent for efficient sampling and learning of symmetric probability densities. Apply to regression, classification, and molecular design.
Geometric Machine Learning for Molecular Medicine
Explore geometric machine learning applications in molecular medicine, focusing on AI models for therapeutic science and drug repurposing using knowledge graphs and contextual approaches.
Accelerating Cryptic Pocket Discovery with Deep Learning
Explore deep learning techniques for accelerating cryptic pocket discovery in protein structures, focusing on simulation, key degrees of freedom, and tools like PocketMiner and AlphaFold.
Malevolent Architect: Only Bad Decisions in Software Development - GeeCON 2022
Explore architectural pitfalls and solutions in software development, covering debugging, logging, burnout, and more. Learn to make informed decisions and navigate challenges effectively.
Maximum Entropy and Species Distribution Modeling - 2007 - Lecture
Explore maximum entropy methods for species distribution modeling, covering theoretical guarantees, experimental tests, and applications in conservation biology.
Information and Decision Theory Explain Neural Pulse Trains - Lecture
Explore information and decision theory's application to neural communication, uncovering insights into pulse trains and channel capacity in the peripheral nervous system.
Behavioral, Neuroscience, and Computational Methods in the Study of Human Speech
Explore modality-specific speech processing through behavioral, brain imaging, and computational methods. Discover evidence challenging conventional theories of abstract linguistic encoding in speech perception.
Implementing Engrams from a Machine Learning Perspective: Matching for Prediction
Explore machine learning approaches to implementing engrams, focusing on matching techniques for predictive modeling in neuroscience and cognitive science.
AI in Precision Oncology: Personalized Treatment Ranking Based on Molecular Information
Explore AI-driven personalized cancer treatment ranking using comprehensive molecular data. Learn about innovative computational methods for precision oncology and targeted therapy selection.
AI Analysis of Super-Resolution Microscopy - Novel Insight Into Subcellular Structure
Explore AI analysis of super-resolution microscopy for novel insights into subcellular structures. Learn about weakly supervised paradigms and their potential in accelerating nanoscale architecture exploration.
Machine Learning Insights into Antimicrobial Efficacy and Resistance
Explore machine learning innovations addressing antimicrobial resistance challenges in understanding, diagnosis, and treatment. Gain insights from Dr. Jason H. Yang on combating this global health threat.
Introducing REM-I: Deepcell's AI-Powered Instrument for Single Cell High-Dimensional Morphology Analysis
Explore AI-powered single-cell morphology analysis with REM-I, combining high-resolution imaging and deep learning for comprehensive cellular insights.
Leveraging What We Know: Knowledge Discovery and Knowledge Exploitation as Complementary Aspects of Explainable AI
Explore how Large Language Models and neuropsychiatric knowledge can be leveraged for psychiatric evaluation, diagnosis, and treatment prediction in various mental health conditions.
Setting the Precedent for Artificial Intelligence and Full Laboratory Automation
Explore advancements in AI and automation for medical laboratories. Learn about improved results, faster turnaround times, and innovative systems like Colibrí™, WASPLab®, and Radian® from industry experts.
Challenges and Opportunities of Artificial Intelligence in Neuroscience
Explore AI's impact on neuroscience with experts discussing challenges, opportunities, and explainability. Gain insights into the intersection of artificial and natural intelligence.
Neural Network Models of Visual Learning and Development
Explore neural network models for understanding visual learning and development in natural and artificial intelligence with MIT postdoctoral fellow Chengxu Zhuang.
Towards Multi-system Neural Network Models of Brain Functions
Explore multi-system neural networks for cognitive neuroscience, combining modules for vision, audition, and more. Gain insights into brain functions through advanced computational modeling.
Explainable AI with Applications for Brain Imaging and Drug Discovery
Explore explainable AI techniques for deep neural networks, focusing on saliency backpropagation. Learn applications in biomarker discovery from fMRI data and drug mechanism prediction.