We record a vanishing phenomenon for exact (non-Monte-Carlo) Weingarten calculus computations on SO(m), encountered while searching for non-local closing constructions for the residual 3⁻³⁴ discrepancy in reconstructing Nissim's SO(3) deconfinement tube. Call a plaquette a 4-cycle of directed edges, and say it is doubl...
Martín Baca· Zenodo (CERN European Organi...· 0 citations
guv-calcs is an open-source Python scientific computing library for physically based modeling of germicidal ultraviolet (GUV) light in indoor environments, with a focus on far-UVC (200–235 nm) applications. The library provides core numerical tools for representing lamps, spatial geometry, calculation planes and volume...
Vivian Belenky, Holger Claus· Zenodo (CERN European Organi...· 0 citations
Modern deep learning accelerators (GPUs, TPUs) are fundamentally constrained by the von Neumann memory wall: over 90% of total inference energy and latency is consumed by shuttling high-precision matrix weights across off-chip memory hierarchies (HBM3e, GDDR6) rather than executing arithmetic operations. Furthermore, a...
Christian Duguay, Alix· Zenodo (CERN European Organi...· 0 citations
roseNNa is now a code generator. A model is lowered to Fortran 2008 or C11 with literal loop bounds, no runtime shape logic, no allocation and no mutable global state, so infer inlines into a solver's own compute kernel -- including a device kernel. The previous runtime library (fLibrary/) is retired. It parsed a model...
Ajay Bati, Spencer H. Bryngelson· Zenodo (CERN European Organi...· 0 citations
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Photonic logic gates, essential for next-generation photon computing, are currently hindered by limited dynamic control, high power consumption, and architectural complexity. Here, we demonstrate a non-volatile, reconfigurable optoelectronic logic device based on a van der Waals heterostructure of ferroelectric α-In₂Se...
Erratum notice (v1.6). This version repairs five defects in the v1.5 record. It is a build, labelling and open-problem erratum: no theorem, proposition, conjecture, or numerical value of v1.5 is altered by it. Concept DOI is preserved (10.5281/zenodo.19941678); v1.5 (10.5281/zenodo.22717792) is superseded. (1) Wrong bu...
papanokechi papanokechi· Zenodo (CERN European Organi...· 0 citations
Overview This dataset provides a geospatially enriched version of the EVRPTW benchmark instances of Schneider et al. (2014). It is intended for evaluating routing algorithms for electric vehicles when route optimization and physically based energy consumption must be studied together. Every node of every instance (depo...
Iyed GUIZENI, Mariem Belhor· Zenodo (CERN European Organi...· 0 citations
We present a systematic experimental study of what an observer with a restricted read channel can learn about a deterministic source whose full state is inaccessible to him. The source is a 12-node icosahedral cluster evolving under a discrete second-order update rule; the observer reads a subset of nodes through a fix...
Fedor Kapitanov· Zenodo (CERN European Organi...· 0 citations
Modern deep learning accelerators (GPUs, TPUs) are fundamentally constrained by the von Neumann memory wall: over 90% of total inference energy and latency is consumed by shuttling high-precision matrix weights across off-chip memory hierarchies (HBM3e, GDDR6) rather than executing arithmetic operations. Furthermore, a...
Christian Duguay, Alix· Zenodo (CERN European Organi...· 0 citations
We record a vanishing phenomenon for exact (non-Monte-Carlo) Weingarten calculus computations on SO(m), encountered while searching for non-local closing constructions for the residual 3⁻³⁴ discrepancy in reconstructing Nissim's SO(3) deconfinement tube. Call a plaquette a 4-cycle of directed edges, and say it is doubl...
Martín Baca· Zenodo (CERN European Organi...· 0 citations
A comprehensive conceptual engineering design specification for a next-generation foiling vessel architecture. The Gen-X system transitions marine transport from rigid mechanical structures to an integrated biomimetic platform. By unifying an indestructible, optically linked carbon nanotube (CNT) triple-core computing...
David Michael Seagal· Zenodo (CERN European Organi...· 0 citations
A deep learning-based LED detection scheme for a mobility-aware MIMO-OFDM system is proposed, which enables long-range MIMO-OFDM communication over distances of up to 22 m while maintaining a low error rate at a receiver speed of 3 m/s.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026
