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Researchers Introduce ‘Colossal-AI’: A PyTorch-Based Deep Learning System For Large-Scale Parallel Training

Deep learning models are already revolutionizing the way we think about AI. One such type is the 'transformer model,' which takes an attention mechanism...

USTC Researchers Introduce A Recursively Embedded Atom Neural Network (REANN) Model To Improve Existing Machine Learning Potential Surface Frameworks

Machine Learning has been extensively used in developing accurate interatomic potentials based on initial data of the given chemical system. Atomic Neural Networks(ANN) have...

Recent Studies Find Ways To Demystify AI Black Boxes

Introduction Deep learning neural networks, which are at the heart of modern artificial intelligence, are frequently characterized as "black boxes" with mysterious inner workings. However,...

Researchers From Edinburgh and Oxford Propose ‘Dist2Cycle’: A Simplicial Neural Network For Homology Localization

Background of GNNs and Simplicial Complexes A graph is a type of data structure that consists of two components, vertices, and edges. Graph Neural Network...

MIT’s Latest AI Research Using Deep Neural Networks Explains How The Brain Processes Language Works

Language Modelling utilizes various statistics and probability techniques to predict the sequence of words occurring in a sentence. These models are widely used in...

Researchers Introduce ‘AugMax’: An Open-Sourced Data Augmentation Framework To Unify The Two Aspects Of Diversity And Hardness

Data augmentation Data augmentation in machine learning is a technique that helps reduce overfitting. It increases the amount of data by adding slightly modified copies...

Apple AI Researchers Propose ‘Plan-then-Generate’ (PlanGen) Framework To Improve The Controllability Of Neural Data-To-Text Models

In recent years, developments in neural networks have led to the advance of data-to-text generation. However, their inability to control structure can be limiting...

Researchers Open-Source ‘TorchDrug’: A PyTorch-Based Machine Learning Platform Designed For Drug Discovery

From drug findings to clinical trials, drug discovery is a long and costly process, taking on average 10 years and $2.5 billion to develop...

MIT Researcher’s Machine Learning Study Can Save Seaweed

Seaweed is very popular in East Asian cuisines, and it has enormous promise as a long-term food supply for the world's rising population. Seaweed,...

Rutgers University’s AI Researchers Propose A Slot-Based Autoencoder Architecture, Called SLot Attention TransformEr (SLATE)

DALLĀ·E has shown an impressive ability of composition-based systematic generalization in image generation, but it requires the dataset of text-image pairs and provides compositional...

Microsoft AI Research Releases ‘ORBIT’ Dataset: A Real-World Few-Shot Dataset for Teachable Object Recognition

Object recognition algorithms have come a long way in recent years, but they still require training datasets containing thousands of high-quality, annotated examples for...

ByteDance Proposes An Impressive Multi-Object Tracking Architecture

Multi-object tracking (MOT) involves identifying and following objects as they move about in videos. Currently, available methods obtain identities by associating detection boxes whose...

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