A type of artificial intelligence that focuses on designing systems that can learn from and make decisions based on data.
This research paper focuses on the convergence rates of loss and uncertainty-based active learning algorithms. The authors first provide conditions for a convergence rate guarantee and apply this to linear…
Continue readingThis academic article explores the Partial Optimal Transport (POT) problem – a mathematical problem concerning the transportation of unbalanced measures or quantities. The authors critique the current state-of-the-art Sinkhorn algorithm…
Continue readingThe article presents a study on metalearning and multitask learning, focusing on tasks related by a shared representation in a binary classification setting. The key question is to determine how…
Continue readingThis paper introduces a new perspective on stochastic optimal control in dynamical systems, a key challenge in sequential decision-making. The authors propose a method of control as Markovian score climbing…
Continue readingThe article presents a novel approach to multi-relational clustering, which is a challenging task due to the diverse semantic information in multi-layer graphs. The authors propose a graph filter based…
Continue readingThe study introduces ‘WellFactor’, a method that creates comprehensive patient profiles using not only traditional medical records but also diverse data sets from healthcare web portals. The approach uses constrained…
Continue readingDiffusion Reward is a novel framework that learns rewards from expert videos for reinforcement learning tasks. The system leverages conditional video diffusion models to solve complex visual reinforcement learning problems….
Continue readingThe article introduces a novel coarse-to-fine approach for 3D instance segmentation, named Spherical Mask. It is based on spherical representation, which overcomes limitations of existing methods, such as instance size…
Continue readingThe article presents CaRe-CNN, a cascading refinement convolutional neural network (CNN) model for segmenting myocardial infarcts and microvascular obstructions in magnetic resonance imaging (MRI). The model is fully 3D and…
Continue readingThe article presents GAvatar, a method for generating high-fidelity 3D avatars from text prompts. The method utilizes a new 3D representation, 3D Gaussian Splatting, to create realistic, animatable avatars. The…
Continue readingLooks like you're using an ad blocker. Please support us by disabling these ad blocker.
