Gianni Franchi @ ICLR2024 @GianniFranchi10
I am working as an assistant professor at @ENSTAParis. I teach #ComputerVision and #MachineLearning. My research focuses on understanding #DeepLearning Paris Joined January 2020-
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If you're intrigued by the connection between symmetries and Bayesian Neural Networks, or keen to delve deeper into Uncertainty Quantification and DNNs, join us for our poster session this Wednesday morning at Poster 211! #iclr2024 @iclr_conf #uncertainty
According to @iclr_conf’ stats LLM models used to correct paper do not change the results :)
The talk of @priyald17 at @iclr_conf about AI and climate is really interesting and crucial today. A lot of insights of the impact of AI on climate and how it can help
"make a watercolor painting of mother Teresa fighting against poverty" copilot.microsoft.com/images/create/… copilot.microsoft.com/images/create/… @Abebab @GaryMarcus @ChombaBupe @rao2z
If you're coming to @eccvconf consider our freshly accepted tutorial on: A Bayesian Odyssey in Uncertainty: from Theoretical Foundations 📝 to Real-World Applications 🚀 w/ the amazing @GianniFranchi10 @_olivierlaurent @a1mmer @Pavel_Izmailov More info coming soon #eccv2024
*Variational Learning is Effective for Large Deep Networks* by @ndaheim_ @EmtiyazKhan @ShhhPeaceful @PeterNickl_ @rioyokota @tmoellenhoff A variant of Adam provides a scalable algorithm to train networks via variational inference. arxiv.org/abs/2402.17641
🧪🤖 Super excited to share Synthemol: a #genAI that not only designs new molecule drugs but tells us how to build each molecule in lab. It designed 6 novel antibiotics that we synthesized in Ukraine and experimentally validated nature.com/articles/s4225… @NatMachIntell 🧵
TL;DR: Feed each layer of a transformer with a linear combination of the previous layers' outputs, and it works way better. And the learned coefficients have a cool structure (4th msg in the thread). With the awesome @MatPagliardini, @akmohtashami_a, and Martin Jaggi.
TL;DR: Feed each layer of a transformer with a linear combination of the previous layers' outputs, and it works way better. And the learned coefficients have a cool structure (4th msg in the thread). With the awesome @MatPagliardini, @akmohtashami_a, and Martin Jaggi.
One year ago, we first introduced BEHAVIOR-1K, which we hope will be an important step towards human-centered robotics. After our year-long beta, we’re thrilled to announce its full release, which our team just presented at NVIDIA #GTC2024. 1/n
1/ Given high-dim time series data (e.g., video, text), we'd like to know "what happens in the future?" and "what happened between A and B?" Turns out temporal contrastive learning provably answers these questions! Paper+Code: arxiv.org/abs/2403.04082 Backstory and details below
Un poste de maître de conférences en IA et optimisation est ouvert au Cnam. Si vous travaillez sur des thématiques liées à la robustesse des modèles, l'explicabilité, l'apprentissage de représentations, l'apprentissage par renforcement, n'hésitez pas à me contacter !
Interested in DeepFakes? 👉Check out the 2nd Workshop and Challenge on DeepFake Analysis and Detection at @CVPR! 🕐 Deadline for paper submissions is March 1st. See the website for more: dfad.unimore.it @d_kangin, T. Glaser, A. Nicolosi, P. Angelov, @THassner
Excited to share our new paper arxiv.org/abs/2402.10877 (Oral, ICLR 2024, w/ @tom4everitt, @GoogleDeepMind). In it we answer the question, do agents need to learn causal world models? arxiv.org/abs/2402.10877. 🧵
Researchers at Meta recently shared MAGNeT, a single non-autoregressive transformer model for text-to-music & text-to-sound generation capable of generating audio on-par with the quality of SOTA models — at 7x the speed. MAGNeT is open source as part of AudioCraft. Hear audio…
Wowow this is the most advanced Gradio component I've seen 🔥
Wowow this is the most advanced Gradio component I've seen 🔥
Hi, I wonder how to reduce the environmental impact of conference travel. The issue is that we have no choice since journal publications are becoming too long. How can we balance ecological concerns with career progression?
Late announcement, but I'm excited to announce that my PhD thesis is publicly available! In it I give my thoughts on how to approach variational inference in Bayesian neural nets, deep GPs, including discussion on the marginal likelihood and symmetries. arxiv.org/abs/2401.12418
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My student @DavidCharatan published all the code to make figures for both pixelSplat and FlowMap in the respective github repositories, and just published the Figma file that generates the figures in the paper as well: figma.com/file/WLHx9d6qD…
"make a watercolor painting of mother Teresa fighting against poverty" copilot.microsoft.com/images/create/… copilot.microsoft.com/images/create/… @Abebab @GaryMarcus @ChombaBupe @rao2z
Thank you, @KempeLab! It was so much fun working on this paper with you, @andrew_yashi, and @andrewgwils! Full paper thread to come shortly! #AISTATS2024 @NYUDataScience
Great talk by @timrudner at #AISTATS2024 on our joint work with @andrewgwils and @andrew_yashi .
Biases of 📄->🖼️ generative models are usually studied for fixed (and given) categories. With OpenBias we go beyond this, looking for all kinds of biases given some captions and two friends (an LLM and a VQA model)! Great work by @MorenoDinca and the team, check it out! 👇
💡Did you know that Stable Diffusion often generates Mac laptops? 🎉We discover this bias (& many more) in our paper, OpenBias a #CVPR2024 highlight! 🚀We introduce open-set bias detection in T2I generative models, finding new biases. 🗞️arxiv.org/abs/2404.07990 💻Code coming soon
If you're coming to @eccvconf consider our freshly accepted tutorial on: A Bayesian Odyssey in Uncertainty: from Theoretical Foundations 📝 to Real-World Applications 🚀 w/ the amazing @GianniFranchi10 @_olivierlaurent @a1mmer @Pavel_Izmailov More info coming soon #eccv2024
just noticed: 4 out of 5 PC chairs and 8 out of 10 board members of @NeurIPSConf work for AI megacorporations. does this composition truly represent the community?
@paulwgoldberg @NeurIPSConf "private-sector investment" is an interesting euphemism for this situation. similarly, the suggestion that academic research outside of industry is "kept on life support by govt. grants" is just plain absurd
Discrete steps of the probability density path generated by the DDPM forward diffusion process (ver. 1.0 complete draft). Useful mental picture for both diffusion and flow matching (with its continuous probability density path). Shoutout to @ArashVahdat and company for their…
*Variational Learning is Effective for Large Deep Networks* by @ndaheim_ @EmtiyazKhan @ShhhPeaceful @PeterNickl_ @rioyokota @tmoellenhoff A variant of Adam provides a scalable algorithm to train networks via variational inference. arxiv.org/abs/2402.17641
🧪🤖 Super excited to share Synthemol: a #genAI that not only designs new molecule drugs but tells us how to build each molecule in lab. It designed 6 novel antibiotics that we synthesized in Ukraine and experimentally validated nature.com/articles/s4225… @NatMachIntell 🧵
One year ago, we first introduced BEHAVIOR-1K, which we hope will be an important step towards human-centered robotics. After our year-long beta, we’re thrilled to announce its full release, which our team just presented at NVIDIA #GTC2024. 1/n
The only question reviewers should be asking themselves: "Is the community better off with this paper, or without it?" inappropriate reasons for rejection include: not beating SOTA, bad writing, minor flaws, no theory yet good results, incomplete citations (easily fixed),.....
"Learning to act in noisy contexts using deep proxy learning" Talk video now online! youtu.be/IGK9RL5KoEc?si… Slides: gatsby.ucl.ac.uk/~gretton/paper… from the Series on Modern AI at NYU engineering.nyu.edu/academics/depa… Based on papers: arxiv.org/abs/2105.04544 arxiv.org/abs/2106.03907
We are looking for a post-doc to work on AI, reasoning and LLMs for Amazon Robotics. DM if you're interested.
The deadline is this Friday. Looking forward to your applications!
🚀 Exciting Opportunity Alert! 🚀 🔍 Join us as a Postdoctoral Researcher (fully funded) at the Helmholtz Munich Institute for Explainable Machine Learning and TUM Chair of Interpretable and Reliable Machine Learning! @TU_Muenchen @Helmholtz_Munich @ELLISforEurope
ACCV 2024 deadline added: July 2nd, 2024. accv2024.org
1/ Given high-dim time series data (e.g., video, text), we'd like to know "what happens in the future?" and "what happened between A and B?" Turns out temporal contrastive learning provably answers these questions! Paper+Code: arxiv.org/abs/2403.04082 Backstory and details below
Signed. A good idea for safety in protein design (AI powered or not): regulate and control the protein synthesis machines and firmware, not the AI research itself. This is an idea I promoted at the UK AI Safety Summit.
AI for biology has the potential to help solve some of the most important problems facing our society. Scientific openness will be critical for our field to progress. As scientists engaged in this work, with more than 90 signatories across the world, we are advancing a framework…
After 3 years @Tesla and Optimus, I am thrilled to announce that I joined Hugging Face to start an ambitious open robotics project! (open as in open-source, not as in Open AI) Looking for engineers to build real robots in Paris 🇫🇷 apply.workable.com/huggingface/j/… 🤖🤗
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