We're the Yue Lab at @Caltech with PI @yisongyue!
We work on #MachineLearning for science and engineering applications 🤖 🧠 💻 Tweets by students & postdocs!
Tokenization (aka the root of suffering, iykyk) has gotten a terrible rap this past week😅 but in nascent fields this rap is wack🌶️
I am ecstatic to share➡️TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis
TOTEM learns discrete time tokens (not patches!!)
Excited to share our work on symbolic music generation: https://t.co/5oDHyfTzhC!
We introduce a symbolic music generator with non-differentiable rule guided diffusion models, enabling musicians to effectively use it as a compositional tool.
Website: https://t.co/pYQkeDTe40. 🧵👇
I’ll be joining @GeorgiaTech as an Assistant Professor in @GTaerospace in January 2024!! Deep thanks to my PhD advisors Ryan Eustice, Jessy Grizzle and @GhaffariMaani, my postdoc advisors Soon-Jo Chung and @yisongyue, and all my group members at @UMRobotics and @Caltech.
Today's lab meeting reminder 😂
Coming to you live from Pasadena, it's Friday Night Live with your hosts @SaberaTalukder & @vdorbs. In tonight's top story @yeh_im_excited returns from Rwanda with the latest ICLR tidbits 👀 What ML news hides in plain sight? Tune in to find out!
All animals behave in 3D - we discover 3D poses directly from multi-view videos without requiring annotations.
Essentially videos -> 3D keypoints + connections
We will be @CVPR on June 21!
BKinD-3D Paper: https://t.co/smkf3IgFQ6
Co-first-authors Lili Karashchuk & @_AmilDravid
I am honored to serve as Senior PC for #ICLR2024. Looking forward to serving with @_beenkim (General Chair) and a fantastic PC cast (@YizhouSun, @swarat, @EmtiyazKhan, & Katerina Fragkiadaki). Hope to see you all in Vienna!
Conformal Generative Modeling on Triangulated Surfaces
A general framework that can reliably train probability distributions on a wide range of complicated manifolds.
1st Author: @vdorbs
Project: https://t.co/QkR8opCkDB
We are thrilled to announce "automatic gradient descent"---a neural network optimiser without hyperparameters. AGD trains out-of-the-box and at ImageNet scale.
paper: https://t.co/sVtqUg0ehy
PyTorch: https://t.co/8syS5bh3Vj
1/5
GUYS the @CosyneMeeting workshop program just dropped 🥳
AND @EricMTrautmann's + my workshop "Taming Complexity: Discovering Interpretable Latent Spaces in Human Brains & Behaviors" will be on your Mont Tremblant menu🧑🍳
Too early to say #Cosyne2023? 🙊🤫
https://t.co/jozcb7Xvdj
NeurIPS officially ended yesterday 😭 and it was 🔥 both in person and virtually! I enjoyed seeing old faces and meeting so many new ones ♥️
I put together some topics + papers that piqued my interest and maybe they'll pique yours too🤗
https://t.co/lwjRQzO93B
If you are at #NeurIPS2022 and interested in ML for bio/proteins, check out our poster “Pretrained protein language model transfer learning: is the final layer representation what we want?” @workshopmlsb tomorrow (Room 288 - 289) @avapamini@KevinKaichuang@alexijielu
Policy Optimization with Linear Temporal Logic Constraints
https://t.co/Q0iHaZ5KIk
Appearing at @NeurIPSConf Poster Session 1 (Tuesday 11am-1pm, Hall J #719)
We provide a framework to train policies to satisfy complex tasks specifications expressed in linear temporal logic.
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