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3,069 papers
On graph discrimination it is proved a matching limitation: on graphs where every edge sees the same number of shortest cycles of the same length, the descriptor becomes constant and any model built on it collapses back to the 1-WL bound.
DronesCATS-Agent, an architecture where the MLLM is a swappable component, and DroneCATS, a benchmark treating the model as the independent variable are introduced, an architecture where the MLLM is a swappable component and DroneCATS, a benchmark treating the model as the independent variable.
Workload Aware Column Imprint-Hash Join WACI-HJ is presented, which uses a workload-aware approach to accelerate hash joins and shows 1%, 38%, and 49% gain in CPU, RAM, and I/O, respectively.
The goal of this research is to investigate and develop embedded architectures for edge computing applications. The project targets HW/SW hybrid platforms, composed of FPGA logic coupled with embedded processors, and focuses on two aspects which are critical to IoT sensor-based settings. On the one hand, it involves th...
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A randomized combinatorial algorithm that solves MSRP on unweighted directed graphs in $\tilde{O}(m\sqrt{\sigma n} + \sigma n^2)$ time, with all the output distances correct with high probability.
DETR, an end-to-end detector derived from the Real-Time Detection Transformer, combines efficient local feature extraction with partial-channel global interaction to improve multi-scale representation while reducing the parameter count of the backbone.
A formalized privacy-aware scheduling perspective is proposed that incorporates latency, energy consumption, cost, node trustworthiness, data sensitivity, privacy leakage risk, reliability and auditability into a unified decision model.
The proliferation of Internet of Things (IoT) ecosystems has significantly increased the attack surface of cyber-physical systems, leading to the emergence of large-scale botnets that exploit device vulnerabilities for distributed and persistent attacks. This survey comprehensively reviews state-of-the-art techniques t...
This work proposes LumiCharge, a novel atomic charge prediction framework that incorporates high-order spherical harmonics convolutions and explicitly models multibody interactions, and demonstrates exceptional extrapolation capability and robustness across molecules of varying sizes, effectively overcoming the limitat...
PepBAN is introduced, a deep learning framework for modeling PepPI predictions that effectively learns the pattern of pairwise local interactions, enables the identification of key residues participating in the peptide-protein interactions, and offers an intuitive approach to interpret the underlying mechanisms of PepP...
This study proposes SynGFN, which models molecular design as a cascade of simulated chemical reactions, enabling the assembly of molecules from synthesizable building blocks, as a bridge linking molecular design and synthesis, accelerating exploration and producing diverse, synthesizable, high-performance molecules.
Results indicate that BF3 antagonists can synergize with the LBP antagonist to amplify conformational flexibility in H12 and induce anticorrelated dynamics of H12 with H3 and H4, suggesting a promising avenue for enhancing the efficacy and overcoming the resistance in castration-resistant prostate cancer treatment.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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