Yi Zhou
@YiZhou37PhD candidate focused on uncertainty-based radar and vision fusion in autonomous driving and intelligent transport
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Control physics-based characters at interactive rates to climb over tables and more. No learning! Key ideas: (a) partwise MPC: switch between full-body and factored body-part MPC as convenient; (b) strategy guidance via sparse contact keyframes. SCA 2024 cs.ubc.ca/~van/papers/20…
Looking forward to presenting #RadarFields later this week at #SIGGRAPH2024. We learn 3D geometry directly from 2D raw radar measurements in frequency space, instead of processed radar point clouds😀. Also, no volume rendering needed here. This allows us to access much higher…
If you missed my talk on 3D Human Foundation Agents at Stanford yesterday and want to check it out, here's the recording: acorn.stanford.edu/SCIEN/video/20…
Ever wondered what the world looks like beyond your training data? Thrilled to release @xuefeng_du's latest #NeurIPS2023 paper: DREAM-OOD, a cool framework for crafting photo-realistic OOD images from any in-distribution dataset. Dive in! [1/n] 📄 Paper: arxiv.org/abs/2309.13415
Go to Google Scholar and look up ‘As an AI language model” -“ChatGPT”’
A Large Language Model trained on scientific papers. Type a text and galactica.ai will generate a paper with relevant references, formulas, and everything. Amazing work by @MetaAI / @paperswithcode
🪐 Introducing Galactica. A large language model for science. Can summarize academic literature, solve math problems, generate Wiki articles, write scientific code, annotate molecules and proteins, and more. Explore and get weights: galactica.org
📢Huge update to Gentle Introduction to Conformal Prediction📢 arxiv.org/abs/2107.07511 Notebooks for EVERY example, easy-2-run WITHOUT model/data download. Open+run in Colab!✅ New repo here: github.com/aangelopoulos/… New sections on time-series and risk control!✅ More in 🧵
ICML Workshop on Distribution Free Uncertainty Quantification Tutorial: sites.google.com/berkeley.edu/d… Schedule/Talks: sites.google.com/berkeley.edu/d… Papers: sites.google.com/berkeley.edu/d…
Reminder that the ICML Workshop on Distribution-Free Uncertainty Quantification starts TOMORROW! dfuq.rocks/22 We have 70 awesome papers on UQ for time-series, object detection, distribution shift, and more. All are welcome in Room 308!
impressive
Radio2Speech: High Quality Speech Recovery from Radio Frequency Signals abs: arxiv.org/abs/2206.11066 project page: zhaorunning.github.io/Radio2Speech/
"a raccoon astronaut with the cosmos reflecting on the glass of his helmet dreaming of the stars" @OpenAI DALL-E 2
Chief AI Scientist Yann LeCun (@ylecun) is sketching an alternate vision for building human-level AI. LeCun proposes that the ability to learn “world models” — internal models of how the world works — may be the key. Learn more: ow.ly/I5rR50I1KKl
Natural neighbor interpolation (Robin Sibson) is a generalization of piecewise linear interpolation to higher dimensions. en.wikipedia.org/wiki/Natural_n… en.wikipedia.org/wiki/Robin_Sib…
I have spent 6 months to compress 6 years of work into this first paper. I Our white paper on LiDAR requirements for L3 is available Want to thank my team who worked hard to make this available and hoping this will help the industry. $INVZ innoviz.tech/designing-a-le…
nice work
Raw High-Definition Radar for Multi-Task Learning deepai.org/publication/ra… by Julien Rebut et al. #Tensor #Estimator
Distillation: it's not just for ML models! You can also apply similar ideas to datasets.
Dataset distillation enables #ML models to be trained using less data and compute. Today we introduce two novel dataset distillation algorithms and release their distilled datasets, which yield state-of-the-art results for image classification. goo.gle/3GKtomH
This article contains everything you ever wanted to know and more about how people interpret graphs, & it exists largely thanks to @SteveFranconeri’s leadership. The amount of cat-herding he took on to make this happen was tremendous. Thank you Steve!
Dataset distillation enables #ML models to be trained using less data and compute. Today we introduce two novel dataset distillation algorithms and release their distilled datasets, which yield state-of-the-art results for image classification. goo.gle/3GKtomH
This must be where the Bayesians meet up on the weekends
This is such a great article on automotive radar from @bradtem at @Forbes forbes.com/sites/bradtemp…
Oldies but goldies: Jordan, Kinderlehrer, Otto, The Variational Formulation of the Fokker-Planck Equation. Show that heat equation is Optimal Transport flow (i.e. flow of particle systems) minimizing Shannon-Boltzmann entropy. More general entropies lead to non-linear PDEs.
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Who to follow
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Guohao Li (Hiring!) 🐫
@guohao_li -
Armin Mustafa
@ArminMustafa -
Georgia Chalvatzaki
@GeorgiaChal -
Joonho Lee
@junja941 -
Giseop Kim
@GiseopK -
Igor Gilitschenski
@igilitschenski -
Elitsa Krumova
@Eli_Krumova -
Davide Berghi
@DavideBerghi -
Peipei WU
@PeipeiWU19 -
Professor Dr. De Curtò y Díaz
@DeCurto2 -
Dr Steve PhD
@Odds75 -
Shital Shah
@sytelus -
Burak
@Burak__Teke -
Martyna
@Martyna52902854 -
Kavisha Vidanapathirana
@KavishaVid
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