Euclid: High-precision imaging astrometry and photometry from Early Release Observations. I. Internal kinematics of NGC 6397 by combining Euclid and Gaia data

Autor: Libralato, M., Bedin, L. R., Griggio, M., Massari, D., Anderson, J., Cuillandre, J. -C., Ferguson, A. M. N., Lançon, A., Larsen, S. S., Schirmer, M., Annibali, F., Balbinot, E., Dalessandro, E., Erkal, D., Kuzma, P. B., Saifollahi, T., Kleijn, G. Verdoes, Kümmel, M., Nakajima, R., Correnti, M., Battaglia, G., Altieri, B., Amara, A., Andreon, S., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Battaglia, P., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., George, K., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kunz, M., Kurki-Suonio, H., Laureijs, R., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Neissner, C., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tsyganov, A., Tutusaus, I., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Burigana, C., Scottez, V., Scott, D., Smart, R. L.

The instruments at the focus of the Euclid space observatory offer superb, diffraction-limited imaging over an unprecedented (from space) wide field of view of 0.57 deg$^2$. This exquisite image quality has the potential to produce high-precision ast

Externí odkaz: http://arxiv.org/abs/2411.02487

Socially Responsible Data for Large Multilingual Language Models

Autor: Smart, Andrew, Hutchinson, Ben, Amugongo, Lameck Mbangula, Dikker, Suzanne, Zito, Alex, Ebinama, Amber, Wudiri, Zara, Wang, Ding, van Liemt, Erin, Sedoc, João, Olojo, Seyi, Uwakwe, Stanley, Wornyo, Edem, Schmer-Galunder, Sonja, Smith-Loud, Jamila

Publikováno v: ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization, 2024

Large Language Models (LLMs) have rapidly increased in size and apparent capabilities in the last three years, but their training data is largely English text. There is growing interest in multilingual LLMs, and various efforts are striving for model

Externí odkaz: http://arxiv.org/abs/2409.05247

Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning

Autor: Smart, Andrew, Kasirzadeh, Atoosa

Publikováno v: AI & Soc (2024).

What is it to interpret the outputs of an opaque machine learning model. One approach is to develop interpretable machine learning techniques. These techniques aim to show how machine learning models function by providing either model centric local o

Externí odkaz: http://arxiv.org/abs/2409.03632

Autoregressive models for panel data causal inference with application to state-level opioid policies

Autor: Antonelli, Joseph, Rubinstein, Max, Agniel, Denis, Smart, Rosanna, Stuart, Elizabeth, Cefalu, Matthew, Schell, Terry, Eagan, Joshua, Stone, Elizabeth, Griswold, Max, Sorbero, Mark, Griffin, Beth Ann

Motivated by the study of state opioid policies, we propose a novel approach that uses autoregressive models for causal effect estimation in settings with panel data and staggered treatment adoption. Specifically, we seek to estimate of the impact of

Externí odkaz: http://arxiv.org/abs/2408.09012

The Gaia Ultracool Dwarf Sample -- V: The Ultracool Dwarf Companion catalogue

Autor: Baig, Sayan, Smart, R. L., Jones, Hugh R. A., Gagné, Jonathan, Pinfield, D. J., Cheng, Gemma, Moranta, Leslie

We present the Ultracool Dwarf Companion Catalogue of 278 multiple systems, 32 of which are newly discovered, each with at least one spectroscopically confirmed Ultracool Dwarf, within a 100 pc volume-limited sample. This catalogue is compiled using

Externí odkaz: http://arxiv.org/abs/2408.07024