arXiv:2512.08882v1 Announce Type: cross Abstract: The rise of space AI is reshaping government and industry through applications such as disaster detection, border surveillance, and climate monitoring, powered by massive data from commercial and governmental low Earth orbit (LEO) satellites. Federated…
arXiv:2512.07876v1 Announce Type: new Abstract: We present a Fourier-enhanced recurrent neural network (RNN) for downscaling electrical loads. The model combines (i) a recurrent backbone driven by low-resolution inputs, (ii) explicit Fourier seasonal embeddings fused in latent space, and (iii) a…
arXiv:2407.20432v2 Announce Type: replace Abstract: Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some scenarios this is infeasible and alternative methods are needed. Simulation-based inference (SBI) methods address…
arXiv:2512.07877v1 Announce Type: new Abstract: Network-on-Chip (NoC) design requires exploring a high-dimensional configuration space to satisfy stringent throughput requirements and latency constraints.Traditional design space exploration techniques are often slow and struggle to handle complex, non-linear parameter interactions.This work presents a…
arXiv:2502.06909v3 Announce Type: replace Abstract: The Industrial Internet of Things (IIoT) leverages Federated Learning (FL) for distributed model training while preserving data privacy, and meta-computing enhances FL by optimizing and integrating distributed computing resources, improving efficiency and scalability. Efficient IIoT…
MIT researchers identified three cognitive skills that we use to infer what someone really means.
arXiv:2512.07037v2 Announce Type: replace-cross Abstract: Recent image Super-Resolution (SR) models are achieving impressive effects in reconstructing details and delivering visually pleasant outputs. However, the overpowering generative ability can sometimes hallucinate and thus change the image content despite gaining high visual…
arXiv:2409.03505v4 Announce Type: replace-cross Abstract: In the Newsvendor problem, the goal is to guess the number that will be drawn from some distribution, with asymmetric consequences for guessing too high vs. too low. In the data-driven version, the distribution is…
arXiv:2508.02581v2 Announce Type: replace-cross Abstract: Manipulating matter with a scanning tunneling microscope (STM) enables creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM…
arXiv:2509.22462v2 Announce Type: replace Abstract: We propose a reduced-space formulation for optimizing over trained neural networks where the network’s outputs and derivatives are evaluated on a GPU. To do this, we treat the neural network as a “gray box” where…
