Generating scenarios for extreme events, without extreme data
A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.
More from the blog
Bringing foundational models to the front lines of TB screening
Generative AI
Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox
A Blog post by Microsoft on Hugging Face
Flint-interactive: A language for creating interactive data visualizations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
NVIDIA Kumo Relational Outperforms Supervised Machine Learning on Relational Data, No Training Required
A Blog post by NVIDIA on Hugging Face
Related papers
Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
A Simultaneous, Multidisciplinary Development and Design Journey - Reflections on Prototyping
A wayfaring approach for the early concept creation stage of development projects that have a very high degree of intended innovation and thus uncertainty and the importance of including all the involved disciplines (knowledge domains) from the beginning of the project on.
Token-Mol 1.0: tokenized drug design with large language models
Token-Mol is presented, a token-only 3D drug design model that encodes both 2D and 3D structural information, along with molecular properties, into discrete tokens, which introduces a Gaussian cross-entropy loss function tailored for regression tasks, enabling superior performance across multiple downstream application...
RSGPT: a generative transformer model for retrosynthesis planning pre-trained on ten billion datapoints
RSGPT, a generative model pre-trained on ten billion data points, achieving state-of-the-art performance for synthesis planning, and introduces reinforcement learning to capture the relationships among products, reactants, and templates more accurately.