Artificial Intelligence and Robotics
Explore AI and robotics concepts including search algorithms, expert systems, natural language processing, neural networks, and robotic applications through Hindi-language explanations and examples.
Machine Learning
In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each o…
Towards Unsupervised Biomedical Image Segmentation Using Hyperbolic Representations - Jeffrey Gu
Explore unsupervised biomedical image segmentation using hyperbolic representations. Learn about novel self-supervised hierarchical loss and its applications in medical imaging analysis.
AI, Machine Learning and Deep Learning
Explore AI, machine learning, and deep learning concepts, including supervised, unsupervised, and reinforcement learning paradigms. Learn when to use traditional ML or deep neural networks for audio applications.
Curation and Analysis of Annotated Medical Images Across Institutions - Xiaoyuan Guo
Explore techniques for curating and analyzing annotated medical images across institutions, focusing on data sharing challenges, anomaly detection, and OOD-aware image retrieval for improved dataset quality and future analysis.
Data-Efficient AI for Accelerating MRI Acquisition
Explore physics-guided AI techniques for accelerating MRI acquisition, including unsupervised and semi-supervised approaches. Learn about a new 1.5TB dataset for evaluating MRI reconstructions with clinically-relevant metrics.
Computer Vision
Explore machine learning and computer vision fundamentals, advanced neural network architectures, and applications in object detection and semantic segmentation.
Validating Daily Social Media Macroscopes of Emotions
Explore how social media sentiment analysis can accurately measure daily emotional dynamics of online communities, validated through surveys and applied to COVID-19 impact studies.
Blessings of Dimensionality for Gaussian Latent Factor Models
Explore how high-dimensional data analysis can benefit from restricted latent factor overlaps, with applications in brain fMRI and financial markets.
An Example Application of Artificial Neural Networks in Archaeology
Exploring artificial neural networks in archaeology to predict site occupation dates from ceramic assemblages, enabling finer-grained demographic reconstructions and deeper insights into human experiences in the past.
Generative Models for Image Synthesis
Explore cutting-edge generative models for image synthesis, translation, and defect detection. Learn about GANs, unsupervised techniques, and interactive applications in this advanced AI seminar.
Unsupervised Video Interpolation Using Cycle Consistency
Explore cutting-edge unsupervised video interpolation techniques using cycle consistency, including implementation, constraints, and experimental results for improved frame generation.
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
Explore unsupervised keypoint learning techniques for guiding class-conditional video prediction, enhancing the accuracy and efficiency of video generation models.
Unsupervised Meta-Learning for Few-Shot Image Classification
Explore unsupervised meta-learning techniques for few-shot image classification, including task construction, augmentation methods, and performance on benchmark datasets.
Robust Pre-Training by Adversarial Contrastive Learning - CAP6412 Spring 2021
Explore robust pre-training techniques using adversarial contrastive learning, focusing on unsupervised and semi-supervised methods for improved model resilience and accuracy.
Unsupervised Cross-Domain Image Retrieval with Semantic-Attended Mixture-of-Experts
Explore unsupervised cross-domain image retrieval using semantic-attended mixture-of-experts, enhancing retrieval accuracy across diverse visual domains.
Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback - Lecture 1
Explore unsupervised LLM alignment for information retrieval using contrastive feedback, enhancing search capabilities and improving query-document relevance.
Data Thinning to Avoid Double Dipping in Statistical Analysis - Lecture 1
Explore data thinning techniques to prevent double dipping in statistical analysis, with applications in single-cell RNA sequencing and unsupervised learning problems.
Integrating Patient Level Multi-omics Data Using Deep Learning Models
Explore deep learning models for integrating patient-level multi-omics data, focusing on supervised and unsupervised approaches for predicting outcomes and uncovering latent representations in genomics.
Scouter Models for Concept Drift Detection in MLOps
Explore techniques for detecting concept drift in ML models without true labels using Scouter models. Learn to build, manage, and implement this critical MLOps monitoring strategy.
Leveraging LLMs for Unsupervised Dense Retriever Ranking - Dense Retrieval 1
Explore unsupervised dense retriever ranking using LLMs for improved information retrieval techniques in this cutting-edge research presentation.