We concluded OxML 2025 today with the last talk of the MLx Representation Learning & Gen AI track. Rounding everything off we were treated to an exceptional talk from Valentina Pyatkin (Allen Institute for AI & University of Washington). 💬🤖 In “Accelerating the Science of

We continued the MLx Representation Learning & Gen AI track with an insightful talk from Christian Rupprecht, Lecturer at the University of Oxford. 🖼️🤖 In “Foundation models in computer vision – what’s taking so long,” Christian examined the gap between the rapid rise of large

We continued the MLx Representation Learning & Gen AI track with an engaging talk from Yali Du, Senior Lecturer at King’s College London. 🤝🧠 In “Human knowledge for cooperative AI,” Yali explored how embedding human knowledge—such as norms, values, and strategies—can enhance

✨ Final Day of OxML 2025 – MLx Representation Learning & Gen AI. We’re closing out an incredible four days of cutting-edge research, insightful discussions, and global connections here at the University of Oxford’s Maths Institute and online. Day 4 Speakers:.Yali Du – Human

We continued the MLx Representation Learning & Gen AI track with an insightful talk from Mergen Nachin of Meta. 📱🧠 In “Deploying GenAI models on edge devices using PyTorch”, Mergen explored how to bring the power of large generative AI models to mobile and embedded hardware. He

We also had the pleasure of hosting Ashley Edwards, Senior Research Scientist at Google DeepMind. 🎨🎥 In “Generative AI for Images & Videos,” Ashley showcased Genie, a model that learns interactive environments directly from internet video without action labels. She explained

We continued the MLx Representation Learning & Gen AI track with an insightful talk from Gerhard Neumann, Professor at KIT. 🤖🎯 In “State, Action and Policy Representations for Reinforcement Learning,” Gerhard explored how intelligent choice of representations can dramatically

We kicked off the penultimate day of the MLx Representation Learning & Gen AI track with an insightful talk from Abdul Fatir Ansari, Research Scientist at AWS AI Labs. ⏳🤖 In “Representation Learning for Time Series”, Abdul explored how modern machine learning techniques can

Yesterday we were also treated to a fascinating talk from Peyman Milanfar, Distinguished Scientist at Google. 📷🧠 In “Denoising – A Powerful Building Block – from Imaging to Machine Learning,” Peyman explored how state-of-the-art denoising algorithms have evolved from simple.

We continue MLx Representation Learning & Generative AI Day 3 with another incredible lineup of speakers! 🚀. 🎙 Abdul Fatir Ansari (Amazon Web Services (AWS) ) – Representation Learning for Time Series.🎙 Gerhard Neumann (Karlsruhe Institute of Technology (KIT) ) – State, Action

We continued the MLx Representation Learning & Gen AI track with a compelling presentation from David Salinas, researcher at Amazon. 🧮🤖 In “Tabular Foundation Models and AutoML,” David explored how foundation models like TabPFN are reshaping structured data modeling. He

We continued the MLx Representation Learning & Gen AI track with a thought-provoking talk from Yingzhen Li, Research Scientist at DeepMind. 🧠🔍 In “Reasoning with Foundation Models,” Chen examined how large language models can move beyond pattern recognition to support

We continued the MLx Representation Learning & Gen AI track with a fascinating talk from Edward Johns, Senior Lecturer at Imperial College London and Director of the Robot Learning Lab. 🤖🧠 In “Representation Learning & Generative AI in Robotics,” Edward explored how

🎤 Day 2 at OxML 2025 – MLx Representation Learning & is packed with top researchers and exciting talks! . 📌 Edward Johns London). Representation Learning & Generative AI in Robotics.📌Cheng Zhang (Meta). Reasoning with Foundation Models.📌 Yingzhen Li

We continued with a dynamic session from Xuan‑Son Nguyen of Hugging Face. 🤖📦 In “Open-Source Tools for ML on Edge Devices & Robots,” Xuan‑Son explored how open-source frameworks like PyTorch, ONNX, and Transformers can power efficient, real-time machine learning on edge

We then moved onto a sharp and thought-provoking session from Aymeric Dieuleveut, Professor at École Polytechnique. 🎯📏 In “Strengths and Limits of Conformal Prediction,” Aymeric unpacked the power of conformal methods for uncertainty quantification, emphasizing their

We kicked off the first day of the MLx Representation Learning & Gen AI track with an insightful talk by Fazl Barez on the evolving landscape of safe and aligned AI systems. 🤖🧩 In “AI Safety and Alignment,” Fazl broke down key challenges in ensuring AI behavior remains

🎉 We’re excited to kick off an inspiring four days of cutting-edge machine learning, generative AI innovation, and global collaboration — live from the Oxford Mathematical Institute and online around the world!. Today marks Day 1 of the MLx Representation Learning & Gen AI track