Adaptive Attention: Bringing Active Vision into the Camera
Explore innovative camera designs and vision algorithms that mimic animal eyes, enabling adaptive and selective active vision for enhanced imaging capabilities and scene understanding.
Integrating AI and Machine Learning in Life Sciences - Allen School Colloquia
Exploring AI integration in life sciences, covering explainable AI, COVID-19 detection, cancer precision medicine, and biological discovery through advanced machine learning techniques.
Enhancing Human Capability with Intelligent Machine Teammates
Exploring human-machine collaboration to improve performance in complex tasks. Research on computational models enabling machines to understand human teammates and enhance capabilities in various fields.
Computer Vision to Phenotype Human Diseases Across Physical and Molecular Scales
Innovative computer vision algorithms for disease phenotyping across scales, from video-based heart function assessment to spatial transcriptomics and immune cell dynamics, with focus on robust and human-compatible AI.
Machine Learning-based Design of Proteins and Small Molecules
Explore machine learning approaches for protein engineering, focusing on data-driven design to create proteins with desired properties and the challenges of extrapolation in predictive modeling.
Artificial Intelligence for Geometry Processing
Explores deep learning techniques for processing irregular 3D geometric data, addressing challenges in surface reconstruction and geometric modeling. Highlights potential applications and future research directions.
Self-supervising 3D Scene Representations for Perception and Control
Explore 3D scene representation models that learn object permanence, emergence, and dynamics without annotations, supporting language grounding and generalizing across scenes and cameras.
FarmBeats: An AI and IoT Platform for Data-driven Agriculture
Explore FarmBeats, an innovative IoT platform revolutionizing agriculture with AI-driven data collection from sensors, cameras, and drones. Learn how it overcomes connectivity challenges and enhances farm productivity.
Fast and Accurate Deep Neural Networks Training
Exploring LARS and LAMB optimizers for scaling deep learning on supercomputers, enabling faster training and higher accuracy in AI applications across various industries.
Building Machines that Discover Generalizable, Interpretable Knowledge
Exploring program induction as a path to human-like AI, focusing on systems that learn generalizable, interpretable knowledge from limited experience across diverse problem domains.
Learning for Never-before-seen Biomedicine
Exploring machine learning methods for predicting never-before-seen biomedical scenarios, focusing on novel class and cohort situations using ontologies and multiscale knowledge graphs.
Do ImageNet Classifiers Generalize to ImageNet? - Analyzing ML Progress and Challenges
Analyzing ImageNet classifiers' generalization, exploring overfitting and distribution shift in ML benchmarks, and addressing robustness issues like adversarial examples to improve machine learning reliability.
Learning 3D Perception from Single Images - Unifying Learning and Geometry
Exploring unified learning approaches for single image 3D understanding, combining 2D perception with 3D world modeling to enable more comprehensive computer vision systems.
Visual Perception and Navigation in 3D Scenes
Exploring 3D scene understanding and visual navigation for robotics, bridging computer vision and robotics. Discusses representation learning, 3D perception, and future research directions in these intersecting fields.
Reinforcement Learning From Small Data in Feature Space - 2019 ADSI Summer Workshop
Explore reinforcement learning in feature space with small datasets, focusing on innovative approaches and algorithmic foundations presented by Princeton researcher Mengdi Wang.
Deep Learning IV - Advanced Topics in Neural Networks
Explore advanced deep learning concepts with NYU professor Joan Bruna, covering cutting-edge techniques and applications in neural networks and machine learning.
Reinforcement Learning - Lecture 5
Explore advanced reinforcement learning concepts with Stanford's Emma Brunskill, covering cutting-edge techniques and applications in AI decision-making.
Reinforcement Learning IV - Advanced Concepts and Applications
Explore advanced reinforcement learning concepts with Stanford's Emma Brunskill, covering cutting-edge techniques and applications in AI decision-making.
Deep Learning III - Advanced Topics in Neural Networks
Explore advanced deep learning concepts with NYU professor Joan Bruna, covering cutting-edge techniques and applications in neural networks and machine learning.
Reinforcement Learning III - Advanced Concepts and Applications
Explore advanced reinforcement learning concepts with Stanford's Emma Brunskill, covering cutting-edge techniques and applications in AI decision-making.
Reinforcement Learning II - Advanced Concepts and Applications
Explore advanced reinforcement learning concepts with Stanford's Emma Brunskill, covering cutting-edge techniques and applications in AI decision-making.