A formal verification of the math of modern deep learning, written as a Lean 4 blueprint project and shipped as the code it proves. Mathlib's fderiv is the foundation; every layer's backward is derived as a vector-Jacobian product rather than asserted -- dense, ReLU, softmax cross-entropy, 2D convolution, max-pool, Bat...
Brett Koonce· Zenodo (CERN European Organi...· 0 citations
This record contains the complete reproducibility package supporting the manuscript "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study." The study evaluates 12 independently prepared AA6061 hybrid-composite specimens nested within four reinf...
Obinna Onyebuchi Barah, Milon Selvam Dennison, Akpan Samuel Cletus· Zenodo (CERN European Organi...· 0 citations
Tahfiz teachers’ strategies for motivating students to memorize the Qur’an are important for sustaining school tahfiz programs. However, studies specifically describing these strategies in the context of public junior high schools remain limited. This study aimed to analyze the strategies used by tahfiz teachers to mot...
Kurnia Yunil Fitri, Alimir· YASIN· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
This record contains the complete reproducibility package supporting the manuscript "Formulation-holdout validation for reliable machine learning in replicated materials experiments: an AA6061 composite case study." The study evaluates 12 independently prepared AA6061 hybrid-composite specimens nested within four reinf...
Obinna Onyebuchi Barah, Milon Selvam Dennison, Akpan Samuel Cletus· Zenodo (CERN European Organi...· 0 citations
The DDPG-DLPID, an adaptive motion controller, including a Deep Deterministic Policy Gradient (DDPG) reinforcement learning that can acquire the parameters of PID controllers is introduced, which achieves faster response and higher tracking accuracy, while substantially reducing tracking errors under interference condi...
Ling Wang, Yan Shi· SAE technical paper series· 0 citations
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.