Zobrazeno 1 - 10
of 7 099
pro vyhledávání: '"Zanella, P."'
Autor:
Ceriani, Paolo Maria, Zanella, Giacomo
We design and analyze unbiased Markov chain Monte Carlo (MCMC) schemes based on couplings of blocked Gibbs samplers (BGSs), whose total computational costs scale linearly with the number of parameters and data points. Our methodology is designed for
Externí odkaz:
http://arxiv.org/abs/2410.08939
Autor:
Zanella, Mattia
We present a systematic review of some basic results on the derivation of classical epidemiological models from simple agent-based dynamics. The evolution of large populations is coupled with the dynamics of the contact distribution, providing insigh
Externí odkaz:
http://arxiv.org/abs/2410.08610
Autor:
Siddiqui, Shoaib Ahmed, Gaonkar, Radhika, Köpf, Boris, Krueger, David, Paverd, Andrew, Salem, Ahmed, Tople, Shruti, Wutschitz, Lukas, Xia, Menglin, Zanella-Béguelin, Santiago
Large Language Models (LLMs) are rapidly becoming commodity components of larger software systems. This poses natural security and privacy problems: poisoned data retrieved from one component can change the model's behavior and compromise the entire
Externí odkaz:
http://arxiv.org/abs/2410.03055
The Gibbs sampler (a.k.a. Glauber dynamics and heat-bath algorithm) is a popular Markov Chain Monte Carlo algorithm which iteratively samples from the conditional distributions of a probability measure $\pi$ of interest. Under the assumption that $\p
Externí odkaz:
http://arxiv.org/abs/2410.00858
After the recent COVID-19 outbreaks, it became increasingly evident that individuals' thoughts and beliefs can have a strong impact on disease transmission. It becomes therefore important to understand how information and opinions on protective measu
Externí odkaz:
http://arxiv.org/abs/2409.17669
The degree distribution is a key statistical indicator in network theory, often used to understand how information spreads across connected nodes. In this paper, we focus on non-growing networks formed through a rewiring algorithm and develop kinetic
Externí odkaz:
http://arxiv.org/abs/2409.06099
The development of vision-language models (VLMs) for histo-pathology has shown promising new usages and zero-shot performances. However, current approaches, which decompose large slides into smaller patches, focus solely on inductive classification,
Externí odkaz:
http://arxiv.org/abs/2409.01883
Autor:
Khoury, Karim El, Zanella, Maxime, Gérin, Benoît, Godelaine, Tiffanie, Macq, Benoît, Mahmoudi, Saïd, De Vleeschouwer, Christophe, Ayed, Ismail Ben
Vision-Language Models for remote sensing have shown promising uses thanks to their extensive pretraining. However, their conventional usage in zero-shot scene classification methods still involves dividing large images into patches and making indepe
Externí odkaz:
http://arxiv.org/abs/2409.00698
Autor:
Sturm, E., Davies, R., Alves, J., Clénet, Y., Kotilainen, J., Monna, A., Nicklas, H., Pott, J. -U., Tolstoy, E., Vulcani, B., Achren, J., Annadevara, S., Anwand-Heerwart, H., Arcidiacono, C., Barboza, S., Barl, L., Baudoz, P., Bender, R., Bezawada, N., Biondi, F., Bizenberger, P., Blin, A., Boné, A., Bonifacio, P., Borgo, B., Born, J. van den, Buey, T., Cao, Y., Chapron, F., Chauvin, G., Chemla, F., Cloiseau, K., Cohen, M., Collin, C., Czoske, O., Dette, J. -O., Deysenroth, M., Dijkstra, E., Dreizler, S., Dupuis, O., van Egmond, G., Eisenhauer, F., Elswijk, E., Emslander, A., Fabricius, M., Fasola, G., Ferreira, F., Schreiber, N. M. Förster, Fontana, A., Gaudemard, J., Gautherot, N., Gendron, E., Gennet, C., Genzel, R., Ghouchou, L., Gillessen, S., Gratadour, D., Grazian, A., Grupp, F., Guieu, S., Gullieuszik, M., de Haan, M., Hartke, J., Hartl, M., Haussmann, F., Helin, T., Hess, H. -J., Hofferbert, R., Huber, H., Huby, E., Huet, J. -M., Ives, D., Janssen, A., Jaufmann, P., Jilg, T., Jodlbauer, D., Jost, J., Kausch, W., Kellermann, H., Kerber, F., Kravcar, H., Kravchenko, K., Kulcsár, C., Kunkarayakti, H., Kunst, P., Kwast, S., Lang, F., Lange, J., Lapeyrere, V., Ruyet, B. Le, Leschinski, K., Locatelli, H., Massari, D., Mattila, S., Mei, S., Merlin, F., Meyer, E., Michel, C., Mohr, L., Montargès, M., Müller, F., Münch, N., Navarro, R., Neumann, U., Neumayer, N., Neumeier, L., Pedichini, F., Pflüger, A., Piazzesi, R., Pinard, L., Porras, J., Portaluri, E., Przybilla, N., Rabien, S., Raffard, J., Raggazoni, R., Ramlau, R., Ramos, J., Ramsay, S., Raynaud, H. -F., Rhode, P., Richter, A., Rix, H. -W., Rodenhuis, M., Rohloff, R. -R., Romp, R., Rousselot, P., Sabha, N., Sassolas, B., Schlichter, J., Schuil, M., Schweitzer, M., Seemann, U., Sevin, A., Simioni, M., Spallek, L., Sönmez, A., Suuronen, J., Taburet, S., Thomas, J., Tisserand, E., Vaccari, P., Valenti, E., Kleijn, G. Verdoes, Verdugo, M., Vidal, F., Wagner, R., Wegner, M., van Winden, D., Witschel, J., Zanella, A., Zeilinger, W., Ziegleder, J., Ziegler, B.
MICADO is a first light instrument for the Extremely Large Telescope (ELT), set to start operating later this decade. It will provide diffraction limited imaging, astrometry, high contrast imaging, and long slit spectroscopy at near-infrared waveleng
Externí odkaz:
http://arxiv.org/abs/2408.16396
Autor:
Mahlow, Felipe, Zanella, André Felipe, Castañeda, William Alberto Cruz, Sarzi-Ribeiro, Regilene Aparecida
In recent years, Generative Artificial Intelligence (GenAI) has undergone a profound transformation in addressing intricate tasks involving diverse modalities such as textual, auditory, visual, and pictorial generation. Within this spectrum, text-to-
Externí odkaz:
http://arxiv.org/abs/2408.00544