🇳🇱 𝗤𝘂𝗮𝗹𝗰𝗼𝗺𝗺 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 🇳🇱 Excited to join @qualcomm.bsky.social in Amsterdam as a research intern in the Model Efficiency group, where I’ll be working on quantization and compression of machine learning models. I’ll return to Copenhagen in December to start the final year of my PhD.

📯 Best Paper Award at CVPR workshop on Visual concepts for our (@doneata.bsky.social + @delliott.bsky.social) paper on probing vision/lang/ vision+lang models for semantic norms! TLDR: SSL vision models (swinV2, dinoV2) are surprisingly similar to LLM & VLMs even w/o lang 👀 arxiv.org/abs/2506.03994

Check out our new preprint 𝐓𝐞𝐧𝐬𝐨𝐫𝐆𝐑𝐚𝐃. We use a robust decomposition of the gradient tensors into low-rank + sparse parts to reduce optimizer memory for Neural Operators by up to 𝟕𝟓%, while matching the performance of Adam, even on turbulent Navier–Stokes (Re 10e5).

Would you present your next NeurIPS paper in Europe instead of traveling to San Diego (US) if this was an option? Søren Hauberg (DTU) and I would love to hear the answer through this poll: (1/6)

Visited the beautiful UC Santa Barbara yesterday.

Thrilled to announce "Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation" is accepted as a Spotlight (5%) at #ICLR2025! Our model MM-FSS leverages 3D, 2D, & text modalities for robust few-shot 3D segmentation—all without extra labeling cost. 🤩 arxiv.org/pdf/2410.22489 More details👇

☀️ Moved to Pasadena, California! ☀️ For the next five months, I’ll be a Visiting Student Researcher at Anima Anandkumar's group at Caltech, collaborating with her team and Jean Kossaifi from NVIDIA on Efficient Machine Learning and AI4Science.

Recordings of the SSL4EO-2024 summer school are now released! This blog post summarizes what has been covered: langnico.github.io/posts/SSL4EO... Recordings: www.youtube.com/playlist?lis... Course website: ankitkariryaa.github.io/ssl4eo/ [1/3]

New Starter Pack: Pioneer Centre for AI researchers

Come by our poster session tomorrow! 🗓️ West Ballroom A-D #6104 🕒 Thu, 12 Dec, 4:30 p.m. – 7:30 p.m. PST @madstoftrup.bsky.social and I are presenting LoQT: Low-Rank Adapters for Quantized Pretraining: arxiv.org/abs/2405.16528 #Neurips2024

Copenhagen University and Aarhus University meet-up in Vancouver 🇩🇰🇨🇦 #NeurIPS2024

On my way to NeurIPS in Vancouver 🇨🇦 Looking forward to reconnecting with friends and meeting new people. Let me know if you are interested in efficient training, quantization, or grabbing a coffee! #NeurIPS2024

Check out the work our lab in Copenhagen will be presenting at #NeurIPS2024 🌟 @neuripsconf.bsky.social @belongielab.org

Here’s a starter pack with members of our lab that have joined Bluesky

Pre-NeurIPS Poster Session in Copenhagen. Thanks to the Pioneer Centre for AI and @ellis.eu for sponsoring. @neuripsconf.bsky.social #neurips2024

Check out the ELLIS Pre-NeurIPS Fest event today in...🇩🇰Copenhagen! ELLIS Unit Copenhagen is holding their event at the Pioneer Center for AI showcasing #NeurIPS posters and other Denmark-affiliated papers in #AI and #ML. More info: bit.ly/4fRFrAh

I'm recruiting 1-2 PhD students to work with me at the University of Colorado Boulder! Looking for creative students with interests in #NLP and #CulturalAnalytics. Boulder is a lovely college town 30 minutes from Denver and 1 hour from Rocky Mountain National Park 😎 Apply by December 15th!

Join us for the 𝗣𝗿𝗲-𝗡𝗲𝘂𝗿𝗜𝗣𝗦 𝗣𝗼𝘀𝘁𝗲𝗿 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 in Copenhagen! 🗓️ 𝗪𝗵𝗲𝗻: 16:00–18:00, Nov. 22, 2024 📍 𝗪𝗵𝗲𝗿𝗲: Entrance Hall, Gefion, Øster Voldgade 10, 1350 København K. Present or explore European contributions to NeurIPS 2024 and connect with colleagues. 👉 𝗜𝗻𝗳𝗼 & 𝘀𝗶𝗴𝗻-𝘂𝗽: www.aicentre.dk/events/pre-n...

Ever wanted to train your own 13B Llama2 model from scratch on a 24GB GPU? Or fine-tune one without compromising performance compared to full training? 🦙 You now can, with LoQT: Low-Rank Adapters for Quantized Pretaining! arxiv.org/abs/2405.16528 1/4

A new approach to training models in memory-constrained settings, LoQT allows for the pre-training of a 13B LLM on a 24GB GPU without model parallelism, checkpointing, or offloading strategies during training Code: github.com/sebulo/LoQT

Logging on! 🧑‍💻🦋 We're the Belongie Lab led by @sergebelongie.bsky.social. We study Computer Vision and Machine Learning, located at the University of Copenhagen and Pioneer Centre for AI. Follow along to hear about our research past and present! www.belongielab.org