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.
Domain Specific Architectures for Deep Neural Networks: Three Generations of Tensor Processing Units
Exploring three generations of Tensor Processing Units (TPUs) for deep neural networks, highlighting performance improvements and the rise of domain-specific architectures in the post-Moore's Law era.
Better Understanding of Non-convex Methods in Machine Learning
Exploring non-convex optimization in machine learning, focusing on matrix completion and neural network architectures. Insights into algorithmic approaches for complex, high-dimensional models.
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 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.
Embedded Deep Learning Super Resolution on GStreamer Using ONNX Inference Runtime
Explore embedded deep learning super-resolution techniques using ONNX Inference Runtime and GStreamer, covering problem-solving, implementation, and performance analysis.
Using Volcano and Kubernetes for Cutting-Edge AI Deployment
Explore cutting-edge AI deployment using Volcano and Kubernetes, focusing on deep learning frameworks, Ascend chipsets, and efficient job scheduling for advanced machine learning projects.
Sustainable Success - AI's Impact on Humanity and Innovation
Explore AI's transformative impact on humanity with Dr. Srinivas Kishan, a double PhD holder in AI. Discover how this technology can empower us to tackle complex problems and redefine possibilities.
Insight and Inequity by Gagandeep Kang
Exploring health inequities and insights in India, focusing on challenges in data collection, analysis, and implementation for improved public health outcomes.
Novel Statistical and Machine Learning Methods for Single Cell Data Analysis
Explore innovative statistical and machine learning techniques for analyzing single-cell data, enhancing understanding of cellular heterogeneity and biological processes at unprecedented resolution.
Public Health Data Sources for Machine Learning and Examples of Research
Explore public health data sources for machine learning and discover research examples in this informative talk. Learn how to leverage data for innovative health studies and applications.
ML and Health Care - An Obgyn Perspective by Uma Ram
Explore machine learning applications in obstetrics and gynecology from an expert's perspective, focusing on potential benefits and challenges in women's healthcare.
Digital Twins in Healthcare by Anurag Agrawal
Explore the potential of digital twins in healthcare, focusing on their applications, benefits, and impact on patient care, medical research, and healthcare systems optimization.
How to Train Your DragoNN - A Primer on Deep Learning for Regulatory
Explore deep learning techniques for regulatory genomics, focusing on key benefits and applications in analyzing genomic data for improved understanding of gene regulation.
Introduction to Probability, Statistics, Statistical Testing
Explore fundamental concepts of probability, statistics, and statistical testing, essential for understanding data analysis and machine learning in health and disease research.
Data- Access, Analysis and Distillation by K VijayRaghavan
Explore data access, analysis, and distillation techniques for machine learning in healthcare. Learn to harness computational methods for understanding health-related data across multiple domains.
Input, Processing and Output of Massive Metadata from Image Recognition
Explore reactive computing, streaming ML, and deep learning for image recognition. Learn about serverless architecture and real-time data processing with a live demo of software engineering integration.
A Collection of Deep Learning Packages for IoT Devices
Explore deep learning packages for IoT devices, focusing on implementation strategies and practical applications for edge computing and resource-constrained environments.
Compare, Contrast, Contribute: Model Deployment Standards and How You Can Help
Explore ML model deployment standards like PMML, PFA, and ONNX. Learn their features, use cases, and how to contribute to open-source initiatives advancing AI/ML interoperability.