Tootfinder

sp_colocation: Social co-locations (2018)
Network of colocations between peoople, based on the information on which RFID readers received information from the RFID tags. Namely, we define two individuals to be in co-presence if the same exact set of readers have received signals from both individuals during a 20s time window.
This network has 100 nodes and 394247 edges.
Tags: Social, Offline, Unweighted, Weighted, Temporal, Metadata

product_space: Atlas of Economic Complexity export network
Two networks of economic products, where a pair of products are connected if they are exported at similar rates by the same countries. The data are a projection from a bipartite network of nations and the products they export. Edges weights represent a similarity score (called "proximity"). Data based on UN Comtrade worldwide trade patterns. SITC network based on the Standard International Trade Classification and HS …

This https://arxiv.org/abs/2312.03940 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search
This paper studies density-based clustering of point sets. These methods use dense regions of points to detect clusters of arbitrary shapes. In particular, we study variants of density peaks clustering, a popular type of algorithm that has been shown to work well in practice. Our goal is to cluster large high-dimensional datasets, which are prevalent in practice. Prior solutions are either sequential, and cannot scale to large data, or are specialized for low-dimensional data. This paper unif…

Classification of Extremal Dependence in Financial Markets via Bootstrap Inference
Qian Hui, Sidney I. Resnick, Tiandong Wang
https://arxiv.org/abs/2506.04656

Classification of Extremal Dependence in Financial Markets via Bootstrap Inference
Accurately identifying the extremal dependence structure in multivariate heavy-tailed data is a fundamental yet challenging task, particularly in financial applications. Following a recently proposed bootstrap-based testing procedure, we apply the methodology to absolute log returns of U.S. S&P 500 and Chinese A-share stocks over a time period well before the U.S. election in 2024. The procedure reveals more isolated clustering of dependent assets in the U.S. economy compared with China which e…

This https://arxiv.org/abs/2405.15927 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Application based Evaluation of an Efficient Spike-Encoder, "Spiketrum"
Spike-based encoders represent information as sequences of spikes or pulses, which are transmitted between neurons. A prevailing consensus suggests that spike-based approaches demonstrate exceptional capabilities in capturing the temporal dynamics of neural activity and have the potential to provide energy-efficient solutions for low-power applications. The Spiketrum encoder efficiently compresses input data using spike trains or code sets (for non-spiking applications) and is adaptable to both…

A look at Russian GRU Unit 29155's hacking department, which started out in 2012, and its involvement in cyber warfare and disinformation campaigns (The Insider)
https://theins.press/en/inv/281731

Hidden Bear: The GRU hackers of Russia’s most notorious kill squad
Russian GRU Unit 29155 is best known for its long list of murder and sabotage ops, which include the Salisbury poisonings in England, arms depot explosions in Czechia, and an attempted coup d’etat in Montenegro. But its activities in cyberspace remained in the shadows — until now. After reviewing a trove of hidden data, The Insider can report that the Kremlin’s most notorious black ops squad also fielded a team of hackers — one that attempted to destabilize Ukraine in the months before …

Plasma sheath physics: A circuital description, amelioration, and application
Pralay Kumar Karmakar, Subham Dutta, Utpal Deka
https://arxiv.org/abs/2506.03935

Plasma sheath physics: A circuital description, amelioration, and application
A synoptic review of the electrical circuital model-based analysis of laboratory plasma sheaths, alongside their stability features in a realistic broader horizon, is systematically presented herein. It explains the basic physics responsible for the inductive (L_sh), capacitive (C_sh), and resistive (R_sh) properties simultaneously, exhibited by plasma sheaths. The analyzed model sheath behaviors are judiciously described in the light of the state-of-the-art sheath scenarios, illustratively. Th…

eACGM: Non-instrumented Performance Tracing and Anomaly Detection towards Machine Learning Systems
Ruilin Xu, Zongxuan Xie, Pengfei Chen
https://arxiv.org/abs/2506.02007

eACGM: Non-instrumented Performance Tracing and Anomaly Detection towards Machine Learning Systems
We present eACGM, a full-stack AI/ML system monitoring framework based on eBPF. eACGM collects real-time performance data from key hardware components, including the GPU and network communication layer, as well as from key software stacks such as CUDA, Python, and PyTorch, all without requiring any code instrumentation or modifications. Additionally, it leverages libnvml to gather process-level GPU resource usage information. By applying a Gaussian Mixture Model (GMM) to the collected multidime…

Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol
Mohammad Saleh Hasankhani
https://arxiv.org/abs/2506.00223

Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol
Accurate prediction of molecular solubility is a cornerstone of early-stage drug discovery, yet conventional machine learning models face significant challenges due to limited labeled data and the high-dimensional nature of molecular descriptors. To address these issues, we propose LatMixSol, a novel latent space augmentation framework that combines autoencoder-based feature compression with guided interpolation to enrich training data. Our approach first encodes molecular descriptors into a lo…

Performance of the image persistence model for Euclid infrared detectors
B. Kubik, R. Barbier, G. Smadja, S. Ferriol, Y. Conseil, Y. Copin, W. Gillard, S. Dusini, K. Jahnke, E. Prieto, N. Auricchio, E. Balbi, A. Balestra, P. Battaglia, V. Capobianco, R. Chary, L. Corcione, F. Cogato, G. Delucchi, E. Franceschi, L. Gabarra, F. Gianotti, F. Grupp, E. Lentini, S. Ligori, E. Medinaceli, G. Morgante, K. Paterson, E. Romelli, L. Sauniere, M. Schirmer, C. Sirignano G. Testera, M. Trifoglio, A. Troja, L. Valenziano, M. Frailis, M. Scodeggio, J. -C. Barriere, M. Berthe, C. Bodendorf, A. Caillat, M. Carle, R. Casas, H. Cho, A. Costille, F. Ducret, B. Garilli, W. Holmes, F. Hormuth, A. Hornstrup, M. Jhabvala, R. Kohley, D. Le Mignant, P. B. Lilje, I. Lloro, C. Padilla, G. Polenta, J. -C. Salvignol, G. Seidel, B. Serra, A. Secroun, L. Stanco, R. Toledo-Moreo, S. Anselmi, E. Borsato, L. Caillat, C. Colodro-Conde, V. Conforti, J. E. Davies, A. Renzi, F. Dal Corso, S. Davini, A. Derosa, J. J. Diaz, S. Di Domizio, D. Di Ferdinando, R. Farinelli, A. G. Ferrari, F. Fornari, F. Giacomini, O. Krause, F. Laudisio, J. Macias-Perez, J. Marpaud, N. Mauri, R. da Silva, M. Niclas, F. Passalacqua, I. Risso, P. Lagier, A. N. Sorensen, P. Stassi, J. Steinwagner, M. Tenti, C. Thizy, S. Tosi, R. Travaglini, O. Tubio, C. Valieri, S. Ventura, C. Vescovi, J. Zoubian
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