Brief

Researchers have developed CADENCE, a new probabilistic framework designed to infer continuous individual trajectories from extremely sparse data snapshots. This method overcomes the limitations of existing approaches that either require dense longitudinal data or lose individual dynamics when analyzing cross-sectional data. CADENCE anchors latent dynamics to static, individual-level contexts, providing identifiability guarantees for single-timepoint trajectory inference. The framework combines a score-based spatial encoder with a Soft Mixture-of-Experts router to jointly identify individual dynamical parameters and routing functions. Tested on various benchmarks, including biological data, CADENCE matches or surpasses the performance of sequential models trained on dense data. AI

Nvidia has released open-source Ising quantum AI models designed to automate and improve the calibration of quantum processors. These models, which include a vision-language model for proposing calibration actions and CNNs for error correction decoding, are intended to be integrated into existing quantum control stacks. By treating calibration as an AI inference problem, similar to how LLMs are deployed, Nvidia aims to enhance the speed, accuracy, and robustness of quantum hardware operations, while also emphasizing the need for governance and security protocols. AI