@WillLin1028

Research Scientist, Isomorphic Labs

 London, England
scholar.google.com/citations?user=rObgGWIAAAAJ&hl=en
Joined December 2016
  • Tweets7
  • Following66
  • Followers76
New work with @lars__schaaf, @WillLin1028, @wanggrun, and @philiptorr: We optimize neural networks to smoothly represent minimum energy paths and predict transition states for chemical reactions. Compared to the traditional approach, our method shows (i) improved resilience to the initial guess, (ii) easy adaptability to escape local minima, (iii) the ability to capture a complex path on its own, and (iv) potential to generalize to unseen systems. This offers a flexible alternative to discrete methods that could unlock building a universal reaction path predictor. Our paper should appeal to anyone interested in machine learning to advance computational chemistry. Preprint: arxiv.org/abs/2502.15843.
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Are RGB inputs good enough for open-world generalization of object detection? Excited to share our #ICLR2023 paper GOOD -- we show that geometric cues can significantly boost the performance for the task! arxiv.org/abs/2212.11720 (Joint work with @AutoVisionGroup @isDanZhang )

GOOD: Exploring Geometric Cues for Detecting Objects in an Open World

We address the task of open-world class-agnostic object detection, i.e., detecting every object in an image by learning from a limited number of base object classes. State-of-the-art RGB-based...

arxiv.org
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How can we leverage successful pretraining techniques from transformers to improve purely convolutional networks? The answer is *Sparse Convolutions*! Let's see what happens when purely convolutional networks are pretrained with 1.28 million unlabeled images ... 1/7
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Designing BERT for convolutional networks: sparse and hierarchical masked modeling Keyu Tian, Yi Jiang, Qishuai Diao, Chen Lin, Liwei Wang, Zehuan Yuan tl;dr: create image, which looks to CNN same, as transformers -> MIM starts working arxiv.org/abs/2301.03580.pdf
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The paper designs a working MLM style pretraining for convnets! Huge if this really works.
Dmytro Mishkin
@ducha_aiki11 Jan 2023
Designing BERT for convolutional networks: sparse and hierarchical masked modeling Keyu Tian, Yi Jiang, Qishuai Diao, Chen Lin, Liwei Wang, Zehuan Yuan tl;dr: create image, which looks to CNN same, as transformers -> MIM starts working arxiv.org/abs/2301.03580.pdf
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