1 citations · 1 across the 6 of their papers we have counts for
7 papers
DrugTargetWorld: A Synthetic Biobank for Training and Benchmarking AI Scientists
Samuel Margolis, Paul Schmiedmayer, Alan Huang +12
Drug target discovery requires distinguishing molecules that causally drive disease from those that are merely associated with it. Training and evaluating AI agents to perform this…
Vision Meets WiFi: Physics-Grounded Estimation of Volumetric Mechanical Properties
Ali Bahri, Hongliang Li, Soufiane Lamghari +2
Estimating volumetric mechanical properties, including Young's modulus, Poisson's ratio, and density at each voxel, is intrinsically ambiguous from vision alone, as visually simila…
Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation
Juzheng Miao, Cheng Chen, Keli Zhang +3
Semi-supervised learning (SSL) has achieved notable progress in medical image segmentation. To achieve effective SSL, a model needs to be able to efficiently learn from limited lab…
FM-OSD: Foundation Model-Enabled One-Shot Detection of Anatomical Landmarks
Juzheng Miao, Cheng Chen, Keli Zhang +3
One-shot detection of anatomical landmarks is gaining significant attention for its efficiency in using minimal labeled data to produce promising results. However, the success of c…
Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets
Wenlong Lyu, Shoubo Hu, Jie Chuai +1
Bayesian optimization (BO) is widely adopted in black-box optimization problems and it relies on a surrogate model to approximate the black-box response function. With the increasi…
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network
Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang +5
The mobile communication enabled by cellular networks is the one of the main foundations of our modern society. Optimizing the performance of cellular networks and providing massiv…
How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed data sets in IoT while avoiding the need for central data coll…