University of Oxford Researchers Utilize Physics-Aware Machine Learning to Tackle Major Quantum Device Challenge
Quantum devices are those based on the principles of quantum mechanics, and they perform tasks that are not feasible using ...
Tag: Researchers
Researchers from Stanford Developed ADMET-AI: A Machine Learning Platform that Provides Fast and Accurate ADMET Predictions both as a Website and as a Python Package
The combination of enlarging chemical repositories and incorporating generative AI into drug discovery procedures has produced many promising drug candidates. ...
NTU and Meta Researchers Introduce URHand: A Universal Relightable Hand AI Model that Generalizes Across Viewpoints, Poses, Illuminations, and Identities
The constant visibility of hands in our daily activities makes them crucial for a sense of self-embodiment. The problem is ...
Researchers from UT Austin Propose a New Machine Learning Approach to Generating Synthetic Functional Training Data that does not Require Solving a PDE (partial Differential Equations) Numerically
The fusion of deep learning with the resolution of partial differential equations (PDEs) marks a significant leap forward in computational ...
Researchers developing AI to make the internet more accessible
In an effort to make the internet more accessible for people with disabilities, researchers at The Ohio State University have ...
Researchers from Tsinghua University Unveil ‘Gemini’: A New AI Approach to Boost Performance and Energy Efficiency in Chiplet-Based Deep Neural Network Accelerators
Researchers from multiple universities have addressed the challenge of designing large-scale DNN chiplet accelerators, focusing on optimizing monetary cost (MC), ...
Researchers from UT Austin and Meta Developed SteinDreamer: A Breakthrough in Text-to-3D Asset Synthesis Using Stein Score Distillation for Superior Visual Quality and Accelerated Convergence
Recent advancements in text-to-image generation driven by diffusion models have sparked interest in text-guided 3D generation, aiming to automate 3D ...
Researchers from Google Propose a New Neural Network Model Called ‘Boundary Attention’ that Explicitly Models Image Boundaries Using Differentiable Geometric Primitives like Edges, Corners, and Junctions
Distinguishing fine image boundaries, particularly in noisy or low-resolution scenarios, remains formidable. Traditional approaches, heavily reliant on human annotations and ...
Google and MIT Researchers Introduce Synclr: A Novel AI Approach for Learning Visual Representations Exclusively from Synthetic Images and Synthetic Captions without any Real Data
Raw and frequently unlabeled data can be retrieved and organized using representation learning. The ability of the model to develop ...
Alibaba Researchers Unveil Unicron: An AI System Designed for Efficient Self-Healing in Large-Scale Language Model Training
The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Training ...
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