Artificial Intelligence in Society, Medicine, Security & Automotive

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R0:62a6aa3b4882ad9b194a4ae5c97b4d58-Ethics-based auditing of automated decision-making systems: intervention points and policy implications

Ethics-based auditing of automated decision-making systems: intervention points and policy implications

Organisations increasingly use automated decision-making systems (ADMS) to inform decisions that affect humans and their environment. While the use of ADMS can improve the accuracy and efficiency of decision-making processes, ...
R0:8c6cf8db215cbc24a8aec1e0786e1356-AI and the Future of Skills, Volume 1

AI and the Future of Skills, Volume 1

The OECD launched the Artificial Intelligence and the Future of Skills project to develop a programme that could assess the capabilities of AI and robotics and their impact on education ...
R0:a56672bf43097f7a50286448af70703b-Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Isaac Gym offers a high performance learning platform to train policies for wide variety of robotics tasks directly on GPU. Both physics simulation and the neural network policy training reside ...
R0:a8fc240769ba4448b373719f7fbe640d-Do Vision Transformers See Like Convolutional Neural Networks?

Do Vision Transformers See Like Convolutional Neural Networks?

Convolutional neural networks (CNNs) have so far been the de-facto model for visual data. Recent work has shown that (Vision) Transformer models (ViT) can achieve comparable or even superior performance ...
R0:fd224a04984225e4bdd2ae7a7e595529-Human Learn

Human Learn

Machine learning covers a lot of ground but it is also capable of making bad decision. We've also reached a stage of hype that folks forget that many classification problems ...
R0:088528eaae518c6f09835c249f9a8635-The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming -

The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming

We analyze the math fundamentals behind DP and demonstrate the power of it by applying it on two real-world text classification tasks. Furthermore, we compare DP with pointillistic active and ...
R0:f70f5b9bc071317c0c1c9b1d7f122949-Highly accurate protein structure prediction with AlphaFold

Highly accurate protein structure prediction with AlphaFold

Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep ...
R0:30b2132518f44667599cd6f2a486e85c-Model-based Decision Making with Imagination for Autonomous Parking

Model-based Decision Making with Imagination for Autonomous Parking

Autonomous parking technology is a key concept within autonomous driving research. This paper will propose an imaginative autonomous parking algorithm to solve issues concerned with parking. ...
R0:e3d9ea294a21c145042e5f31369de739-CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

CARLA (Counterfactual And Recourse LibrAry), a python library for benchmarking counterfactual explanation methods across both different data sets and different machine learning models. In summary, our work provides the following ...
R0:5e6fade87218b43e4b8d96158080cc85-A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

This paper provides a succinct overview of this emerging theory of overparameterized ML (henceforth abbreviated as TOPML) that explains these recent findings through a statistical signal processing perspective. We emphasize ...
R0:97532435b0393f0a6ae72973cc68382e-How to avoid machine learning pitfalls: a guide for academic researchers

How to avoid machine learning pitfalls: a guide for academic researchers

This document gives a concise outline of some of the common mistakes that occur when using machine learning techniques, and what can be done to avoid them. It is intended ...
R0:94ecd1a3b2168ef2dbb43222545d08bc-YOLOX: Exceeding YOLO Series in 2021

YOLOX: Exceeding YOLO Series in 2021

We switch the YOLO detector to an anchor-free manner and conduct other advanced detection techniques, i.e., a decoupled head and the leading label assignment strategy SimOTA to achieve state-of-the-art results ...

Featured content

R0:8c6cf8db215cbc24a8aec1e0786e1356-AI and the Future of Skills, Volume 1

AI and the Future of Skills, Volume 1

The OECD launched the Artificial Intelligence and the Future of Skills project to develop a programme that could assess the capabilities of AI and robotics and their impact on education ...
R0:f70f5b9bc071317c0c1c9b1d7f122949-Highly accurate protein structure prediction with AlphaFold

Highly accurate protein structure prediction with AlphaFold

Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep ...
R0:94ecd1a3b2168ef2dbb43222545d08bc-YOLOX: Exceeding YOLO Series in 2021

YOLOX: Exceeding YOLO Series in 2021

We switch the YOLO detector to an anchor-free manner and conduct other advanced detection techniques, i.e., a decoupled head and the leading label assignment strategy SimOTA to achieve state-of-the-art results ...
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