Cong Fu
@Cong_Fu_
MLE @Uber | CS PhD @TAMU Deep Learning, Graph Neural Networks, AI for Science. Previously at @UMich @DMAIglobal | Intern @FujitsuAmerica @Uber @NVIDIA
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Excited to share our latest survey paper: "Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems"! 🚀 ArXiv: arxiv.org/abs/2307.08423. Feedback is warmly welcomed! Some highlights are as follows: (1/n)
AI+Science book is now up, After years of work, our book on Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems is available at Foundations and Trends® in Machine Learning. We cover the history of works in the intersection of AI and Science, to…
Our 500+ page AI4Science paper is finally published: Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Foundations and Trends® in Machine Learning, Vol. 18, No. 4, 385–912, 2025 nowpublishers.com/article/Detail…
Our 500+ page AI4Science paper is finally published: Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Foundations and Trends® in Machine Learning, Vol. 18, No. 4, 385–912, 2025 nowpublishers.com/article/Detail…
A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials １．PubChemQCR is the largest publicly available dataset of DFT-based molecular relaxation trajectories, with 3.5 million molecules and over 300 million conformations, including 105 million…
How to become expert at thing: 1 iteratively take on concrete projects and accomplish them depth wise, learning “on demand” (ie don’t learn bottom up breadth wise) 2 teach/summarize everything you learn in your own words 3 only compare yourself to younger you, never to others
Excited and proud mentor moment 💫! A new materials foundation model with two of my undergraduate mentees Montgomery Bohde and Andrii Kryvenko as core authors. For Materials Foundation Models, Invariance V.S. Equivariance? Invariance + Equivariance!
Scientists @TAMU tackle the challenges of structure-based drug design with a new #AI approach. Their #Frag2Seq model applies language models to generate drug molecules fragment by fragment, showing promise in creating more effective target-specific drugs. cbirt.net/revolutionizin…
Each week, we want to highlight @LogConference papers! ✨ Check out "A Latent Diffusion Model for Protein Structure Generation" by @Cong_Fu_ @KeqiangY @limei69990587 Wing Yee Au @mmcthrow Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, and @ShuiwangJi !
Interested in learning about latent diffusion models and how they can be used for efficient protein structure generation? Read the latest blog by @Cong_Fu_ and @KeqiangY to learn more about LatentDiff: portal.valencelabs.com/blogs/post/lat…
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Excited about our latest paper about this incredible transformation. It was a great collaboration led by @ShuiwangJi.
Excited to share our latest survey paper: "Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems"! 🚀 ArXiv: arxiv.org/abs/2307.08423.
Check out our #ICML2023 paper, “Group Equivariant Fourier Neural Operators for Partial Differential Equations” (arxiv.org/abs/2306.05697). We solve PDEs by encoding symmetries in Fourier convolutions (1/3)
Our survey paper providing a unified and timely review on self-supervised learning of GNNs has been accepted by #TPAMI. Welcome to check out the preprint version on arXiv: arxiv.org/abs/2102.10757. Also check out our DIG library: github.com/divelab/DIG. #GNNs #graphs #SSL
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