Multi-Expert Learning Architecture (MELA), A Method To Combine Deep Neural Networks

Researchers at the University of Edinburgh and Zhejiang University have revealed a unique way to combine deep neural networks (DNNs) for creating...

Exploring The Power Of Data In Quantum Machine Learning

Quantum computers have the capability to develop quantum machine learning algorithms. These algorithms can achieve better performance for modeling quantum-mechanical systems such as molecules,...

UC Berkeley Researchers Open-Source ‘RAD’ To Improve Any Reinforcement Learning Algorithm

In Reinforcement Learning (RL), it has always been challenging to learn from visual observations, which is a fundamental yet challenging problem. Despite...

Stanford University Researchers Introduces LUCIDGames, A Computational Technique That Can Predict And Plan Adaptive...

Researchers at Stanford University recently introduced LUCIDGames, a computational technique to predict and plan adaptive trajectories for autonomous vehicles. This technique integrates an algorithm...

Inductive Biases May Bridge The Gap Between Current Deep Learning And Human Cognitive Abilities

At present, machine learning (ML) models find applications in various fields, and many ML systems have achieved remarkable accuracy in a variety...

UC Berkeley Researchers Use AI For Digital Voicing Of Silent Speech

Researchers at UC Berkeley have developed an AI model that detects ‘silent speech.’ The model is based on digital voicing to predict...

HAMLET: A Hierarchical Agent-Based Machine Learning Platform For AI Research And Development

Machine learning (ML) algorithms are widely used as computational tools for solving various real-world problems, including image, audio, and text classification tasks....

Caltech Open-Sources FNO: A Deep Learning Method For Solving PDEs (Partial differential equations)

Caltech's Dolcit group recently open-sourced FNO, Fourier Neural Operator, a deep-learning method for Solving the PDEs (Partial differential equations). FNO being three times faster than...

A New Method To Code Inductive Image Biases Into Models Using CNN And Transformers

Researchers at Heidelberg University have recently proposed a novel method to efficiently code inductive image biases into models while retaining all transformers’...

Allen Institute for AI Introduces TL;DR: An AI Tool That Summarizes Research Papers In...

The Researchers at Allen Institute for Artificial Intelligence (AI2) have developed a new AI model that summarizes text from scientific papers. It...
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