Simone Foti @simo_foti
Postdoc at Imperial College London. Research in latent disentanglement, geometric deep learning, computer vision, and computer graphics. simofoti.com London, England Joined February 2022-
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📣 Deadline Extended – LOGML'26 Due to ICLR conference & NeurIPS deadlines, applications are now open till 10 May'26. 🚀 LOGML @ Imperial College London 📅 13–17 July'26 🎓 Talks 🤝 Projects 🧠 Collaboration 🎉 Networking 🔗 Apply: forms.gle/RjxJHCdKVJF41V…
Are you ready for another incredible edition of LOGML 2026? 🇬🇧 While I’m co-organising the school again, I’ll also be mentoring a project alongside Massimiliano Esposito. Apply now to work with us or any of the other incredible mentors!
📣 Participant Applications Open: LOGML’26, Imperial College London (13–17 July) A week on geometry/topology + ML talks, tutorials, projects & networking. 👩🎓 Students/PhD/Postdocs 💰 Limited fee waivers & travel support 🗓 Deadline: 1 May 2026 🔗 Apply: forms.gle/RjxJHCdKVJF41V…
Our #CVPR2026 work Differentiable Straightest Geodesics [circle-group.github.io/research/DSG/] provides exponential maps for 3D meshes allowing to trace geodesics or parallel-transport vectors. With it, we release DiGeo, a PyTorch differential geometry package: digeo.readthedocs.io. 👇
Huge thanks to the team for making this "straightest" vision a reality: @hippolytever (who developed this for his MSc thesis @ICComputing! 🙌), @Kausta42, Stefanos Zafeiriou, and @tolga_birdal. #CVPR #CVML #AI #Graphics #ML #PyTorch
🛠️digeo: for easy deployment, we make all of this available with our new PyTorch library for differential geometry on meshes. Docs & installation: digeo.readthedocs.io pip-install digeo and be part of the next generation of AI research on 3D meshes! 🚀
It's time to bring 3D meshes into modern machine learning properly! 🛸 Our work solves the non-differentiability of the Exp map on meshes, enabling gradients to flow directly through geodesics. It’s differentiable, GPU-fast, and fully parallelised. circle-group.github.io/research/DSG
Love Geometry & ML and have a nice research project in mind? 📐🤖 Join us at #LOGML2026 as a mentor! Help a brilliant team turn your project idea into a research success story.
🚀 LOGML26— Mentor applications! 📍 Imperial College London | 13–17 July 2026 Mentor a project team. Attend talks, socials, networking events. 💸 Travel support available. Deadline: 18 March 2026(AoE) Apply: logml.ai/apply.html #LOGML #MachineLearning #SummerSchool
Our Geometric Neural Distance Fields will be presented at #CVPR2026: circle-group.github.io/research/NRMF/. @CVPR
We present Neural Riemannian Motion Fields (NRMF) as a promising paradigm for generative modeling of articulated motion. Unlike various diffusion based models, NRMF is useful both in generation and in deployment as a prior across tasks: circle-group.github.io/research/NRMF/. #CVPR #AI #CVML👇
We present Neural Riemannian Motion Fields (NRMF) as a promising paradigm for generative modeling of articulated motion. Unlike various diffusion based models, NRMF is useful both in generation and in deployment as a prior across tasks: circle-group.github.io/research/NRMF/. #CVPR #AI #CVML👇
Months of planning, and it's over in a flash! Seeing #LOGML come to life with such a fantastic group was worth every bit of effort. The collaborative spirit during the projects was exactly what we hoped for. Immense gratitude to all who came and made the week a huge success. 👏
And that's a wrap on the LOGML 2025 Summer School! 🚀 We’ve been quiet on here, but that’s because we were busy with 100 brilliant minds diving deep into geometry, ML, and social activities. 😉
LOGML 2025 is shaping up to be incredible! 🔥 If you're into geometry & ML, this is your chance to dive deep, meet top researchers, and work on projects that matter—all in London 🇬🇧 with an amazing community. Trust me, it's as fun as it is inspiring. Apply now! ⏳👇
🌟Applications open- LOGML 2025🌟 👥Mentor-led projects, expert talks, tutorials, socials, and a networking night ✍️Application form: logml.ai 📅Apply by 6th April 2025 ✉️Questions? [email protected] #MachineLearning #SummerSchool #LOGML #Geometry
@JamesEdwards Good point! Our model isn’t quite ready for super high-res PBR textures due to dataset limits, but we’re working on scaling it up. 🤞 LoD and geometry-driven texture variations are fascinating areas we’re eager to explore with future improvements!
🚨 It's confirmed, "UV-free Texture Generation with Denoising and Geodesic Heat Diffusions" just landed at #NeurIPS2024! No more UV map struggles—just point cloud textures & heat diffusion magic. 🔥 Curious? Keep reading. Oh, and definitely turn up the audio 🎧👇
💡Excited by geometry & ML like our organizing committee?💡 Mentor at LOGML 2025 and help shape projects that can become top publications. It’s academic, social, and seriously fun—Plus, it’s in London 🇬🇧 (July 7-11) and we’ve got you covered. Apply now 👇👇👇
⭐️Mentor applications open⭐️ We're excited to announce that LOGML summer school will return in London: July 7-11 2025. We are seeking mentors to lead group projects at the intersection of geometry and machine learning. Find out more and apply: logml.ai
@lettercastai Oh nice, thank you for making this alternative podcast! Even if it is probably less engaging than the one I added to the video, it better captures the content of the paper. 🤓 Blending the two versions would be amazing 🙂
@lovespurts I appreciate your insights, but the podcast is just a playful way to present our research. Ultimately, the most important endorsement comes from the scientific community that peer-reviewed our work for NeurlPS, which holds more weight than any podcast commentary.
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