IBM

Researchers from IBM, MIT and Harvard Announced The Release Of DARPA...

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Building machines that can make decisions based on common sense is no easy feat. A machine must be able to do more than merely...

Researchers at MIT and IBM Propose an Efficient Machine Learning Method...

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This research summary is based on the paper 'DATA-EFFICIENT GRAPH GRAMMAR LEARNING FOR MOLECULAR GENERATION' Please don't forget to join our ML Subreddit Chemical engineers and...

Adversarial Machine Learning Threat Matrix – A Framework To Defend AI...

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Microsoft, in collaboration with MITRE research organization and a dozen other organizations, including IBM, Nvidia, Airbus, and Bosch, has released the Adversarial ML Threat...

Yale University and IBM Researchers Introduce Kernel Graph Neural Networks (KerGNNs)

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Graph kernel approaches have typically been the most popular strategy for graph classification tasks. Graph kernels can be thought of as functions that measure...

IBM Researchers Showcase Their Non-Von Neumann AI Hardware Breakthrough in Neuromorphic...

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This research summary article is based on the paper. 'Phase-change memtransistive synapses for mixed-plasticity neural computations' Human brains are exceptionally good at remembering and learning...

IBM AI Introduces ‘VanDEEPol’: A Hybrid Model That Combines VDP with...

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'VanDEEPol', a hybrid AI/mechanistic model to predict brain activity and structure from imaging data, is IBM's most recent development in the field of brain...

CogMol: Framework developed by IBM based on deep learning to accelerate...

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The global novel Coronavirus (COVID-19) pandemic is rapidly evolving and expanding. There is still a lot of news coverage about community spread every day. While...

LALE: A Python Library Simplifying Automated Machine Learning

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Whenever any data scientist thinks of developing a pipeline, they try bringing automated machine learning into the picture to make the task easier. However,...

IBM Open Sources ‘CodeFlare’, A Machine Learning Framework That Simplifies AI...

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Data and machine-learning analytics are becoming more widespread, but they grow in complexity with larger datasets requiring much time for configuration. Researchers spend less...

IBM’s Approach Towards Preserving Adversarial Robustness of Machine Learning Systems

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In the real world, machine learning (ML) procedures can be sensitive to adversarial attacks. Algorithms take numeric vectors as inputs. A malicious attack is...