Carnegie Mellon University

Researchers From Microsoft and CMU Introduce ‘COMPASS’: A General-Purpose Large-Scale Pretraining Pipeline For Perception-Action Loops in Autonomous Systems

AI Paper Summary
Humans have the essential cognitive capacity to comprehend the world via multimodal sensory inputs and use this ability to perform a wide range of...

A New Study from CMU and Bosch Center for AI Demonstrated a New Transformer Paradigm in Computer Vision

AI Paper Summary
After leveraging Convolutional Neural Network (CNN) for many years, since the advent of Transformers in Natural Language Processing (NLP), the computer vision community has...

CMU’s Latest Machine Learning Research Analyzes and Improves Spectral Normalization In GANs

AI Paper Summary
GANs (generative adversarial networks) are cutting-edge deep generative models that are best known for producing high-resolution, photorealistic photographs. The goal of GANs is to...

Latest CMU Research Improves Reinforcement Learning With Lookahead Policy: Learning Off-Policy with Online Planning

AI Paper Summary
Reinforcement learning (RL) is a technique that allows artificial agents to learn new tasks by interacting with their surroundings. Because of their capacity to...

CMU Researchers Propose A Computer Vision-Based Approach With Data-Frugal Deep Learning To Optimize Microstructure Imaging

AI Paper Summary
Materials processing is the process of turning raw materials into final items through a sequence of phases or "unit operations." The activities entail a...

Meta AI and CMU Researchers Present ‘BANMo’: A New Neural Network-Based Method To Build Animatable 3D Models From Videos

AI Paper Summary
Previous work on articulated 3D shape reconstruction has frequently relied on specialized sensors (e.g., synchronized multi-camera systems) or pre-built 3D deformable models (e.g., SMAL...

AI Researchers Propose ‘GANgealing’: A GAN-Supervised Algorithm That Learns Transformations of Input Images to Bring Them into Better Joint Alignment

Adobe
The correspondence problem of visual alignment is one that computer vision algorithms must solve for many different applications.It's considered a critical element in Optical...

Researchers Develop A Unified Framework For Evaluating Natural Language Generation (NLG)

AI Paper Summary
Natural language generation (NLG) is a broad term that encompasses a variety of tasks that generate fluent text from input data and other contextual...

CMU AI Researchers Present A New Study To Achieve Fairness and Accuracy in Machine Learning Systems For Public Policy

AI Paper Summary
The rapid rise in machine learning applications in criminal justice, hiring, healthcare, and social service intentions substantially impacts society. These wide applications have heightened...

CMU Researchers Introduce ‘CatGym’, A Deep Reinforcement Learning (DRL) Environment For Predicting Kinetic Pathways To Surface Reconstruction in a Ternary Alloy

AI Paper Summary
It isn't an easy task to design efficient new catalysts. In the case of multiple element mixtures, for example - researchers must take into...

CMU and MIT AI Researchers Present A New Method To Sketch Your Own GAN With A Pencil

AI Paper Summary
Sketching is the most universally accessible way to convey a visual concept. In contrast, creating GAN models has traditionally required knowledge in deep learning...

Researchers at Facebook AI, UC Berkeley, and Carnegie Mellon University Announced Rapid Motor Adaptation (RMA), An Artificial Intelligence (AI) Technique Which Enables Legged Robots...

AI Paper Summary
To achieve success in the real world, walking robots must adapt to whatever surfaces they encounter, objects they carry, and conditions they are in,...
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