4.5k citations · 32.3k across the 207 of their papers we have counts for
12 papers · 1 filter
Hybrid Forecasting of Geopolitical Events
Daniel M. Benjamin, Fred Morstatter, Ali E. Abbas +26
Sound decision-making relies on accurate prediction for tangible outcomes ranging from military conflict to disease outbreaks. To improve crowdsourced forecasting accuracy, we deve…
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities
Charlotte Bunne, Yusuf Roohani, Yanay Rosen +39
The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determ…
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
Juntong Shi, Minkai Xu, Harper Hua +3
Synthesizing high-quality tabular data is an important topic in many data science tasks, ranging from dataset augmentation to privacy protection. However, developing expressive gen…
Learning production functions for supply chains with graph neural networks
Serina Chang, Zhiyin Lin, Benjamin Yan +8
The global economy relies on the flow of goods over supply chain networks, with nodes as firms and edges as transactions between firms. While we may observe these external transact…
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
Siyi Gu, Minkai Xu, Alexander Powers +6
Generating ligand molecules for specific protein targets, known as structure-based drug design, is a fundamental problem in therapeutics development and biological discovery. Recen…
Countrywide natural experiment reveals impact of built environment on physical activity
Tim Althoff, Boris Ivanovic, Jennifer L. Hicks +3
While physical activity is critical to human health, most people do not meet recommended guidelines. More walkable built environments have the potential to increase activity across…
Reverse Image Retrieval Cues Parametric Memory in Multimodal LLMs
Jialiang Xu, Michael Moor, Jure Leskovec
Despite impressive advances in recent multimodal large language models (MLLMs), state-of-the-art models such as from the GPT-4 suite still struggle with knowledge-intensive tasks.…
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf Roohani, Andrew Lee, Qian Huang +6
Agents based on large language models have shown great potential in accelerating scientific discovery by leveraging their rich background knowledge and reasoning capabilities. In t…
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
Tailin Wu, Willie Neiswanger, Hongtao Zheng +2
Deep learning-based surrogate models have demonstrated remarkable advantages over classical solvers in terms of speed, often achieving speedups of 10 to 1000 times over traditional…
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
Serina Chang, Frederic Koehler, Zhaonan Qu +2
A common network inference problem, arising from real-world data constraints, is how to infer a dynamic network from its time-aggregated adjacency matrix and time-varying marginals…
Compositional Generative Inverse Design
Tailin Wu, Takashi Maruyama, Long Wei +4
Inverse design, where we seek to design input variables in order to optimize an underlying objective function, is an important problem that arises across fields such as mechanical…
Equivariant Graph Neural Operator for Modeling 3D Dynamics
Minkai Xu, Jiaqi Han, Aaron Lou +6
Modeling the complex three-dimensional (3D) dynamics of relational systems is an important problem in the natural sciences, with applications ranging from molecular simulations to…