Sort by
Refine Your Search
-
aimed at breakthrough innovations in model capabilities, reasoning, safety, and efficiency. Algorithm & Model Development (LLMs & AIGC): Design and develop novel architectures for large-scale language and
-
include: Advanced Reinforcement Learning: From sample-efficient offline RL to multi-agent coordination and hierarchical RL, we are developing algorithms that can learn complex behaviors and strategies in
-
, it has matured into an established research community seeking automatic, computerized processing of 3D geometric data obtained through measurements or designs. The following developments have shaped
-
in Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted starting date
-
Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted starting date
-
both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate
-
of Excellence for Data-Driven Discovery, applying advanced computational techniques to develop novel therapeutics. This position will work closely with researchers in the Center of Excellence for Data Driven
-
, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
-
train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
-
motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global