Differentially Private Mixture of Generative Neural Networks von Acs, Gergely, Melis, Luca, Castelluccia, Claude, De Cristofaro, Emiliano

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Privacy pitfalls of releasing in-vehicle network data von Gazdag, András, Lestyán, Szilvia, Remeli, Mina, Ács, Gergely, Holczer, Tamás, Biczók, Gergely

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Contextual factors predicting compliance behavior during the COVID-19 pandemic: A machine learning analysis on survey data from 16 countries von Hajdu, Nandor, Schmidt, Kathleen, Acs, Gergely, Röer, Jan P, Mirisola, Alberto, Giammusso, Isabella, Arriaga, Patrícia, Ribeiro, Rafael, Dubrov, Dmitrii, Grigoryev, Dmitry, Arinze, Nwadiogo C, Voracek, Martin, Stieger, Stefan, Adamkovic, Matus, Elsherif, Mahmoud, Kern, Bettina M J, Barzykowski, Krystian, Ilczuk, Ewa, Martončik, Marcel, Ropovik, Ivan, Ruiz-Fernandez, Susana, Baník, Gabriel, Ulloa, José Luis, Aczel, Balazs, Szaszi, Barnabas

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Contextual factors predicting compliance behavior during the COVID-19 pandemic: A machine learning analysis on survey data from 16 countries von Nandor Hajdu, Kathleen Schmidt, Gergely Acs, Jan P. Röer, Alberto Mirisola, Isabella Giammusso, Patrícia Arriaga, Rafael Ribeiro, Dmitrii Dubrov, Dmitry Grigoryev, Nwadiogo C. Arinze, Martin Voracek, Stefan Stieger, Matus Adamkovic, Mahmoud Elsherif, Bettina M. J. Kern, Krystian Barzykowski, Ewa Ilczuk, Marcel Martončik, Ivan Ropovik, Susana Ruiz-Fernandez, Gabriel Baník, José Luis Ulloa, Balazs Aczel, Barnabas Szaszi

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Differentially Private Histogram Publishing through Lossy Compression von Acs, G., Castelluccia, C., Rui Chen

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Privacy-Aware Caching in Information-Centric Networking von Acs, Gergely, Conti, Mauro, Gasti, Paolo, Ghali, Cesar, Tsudik, Gene, Wood, Christopher A.

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MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information von Heyndrickx, Wouter, Mervin, Lewis, Morawietz, Tobias, Sturm, Noé, Friedrich, Lukas, Zalewski, Adam, Pentina, Anastasia, Humbeck, Lina, Oldenhof, Martijn, Niwayama, Ritsuya, Schmidtke, Peter, Fechner, Nikolas, Simm, Jaak, Arany, Adam, Drizard, Nicolas, Jabal, Rama, Afanasyeva, Arina, Loeb, Regis, Verma, Shlok, Harnqvist, Simon, Holmes, Matthew, Pejo, Balazs, Telenczuk, Maria, Holway, Nicholas, Dieckmann, Arne, Rieke, Nicola, Zumsande, Friederike, Clevert, Djork-Arné, Krug, Michael, Luscombe, Christopher, Green, Darren, Ertl, Peter, Antal, Peter, Marcus, David, Do Huu, Nicolas, Fuji, Hideyoshi, Pickett, Stephen, Acs, Gergely, Boniface, Eric, Beck, Bernd, Sun, Yax, Gohier, Arnaud, Rippmann, Friedrich, Engkvist, Ola, Göller, Andreas H., Moreau, Yves, Galtier, Mathieu N., Schuffenhauer, Ansgar, Ceulemans, Hugo

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MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information von Heyndrickx, Wouter, Mervin, Lewis, Morawietz, Tobias, Sturm, Noe, Friedrich, Lukas, Zalewski, Adam, Pentina, Anastasia, Humbeck, Lina, Oldenhof, Martijn, Niwayama, Ritsuya, Schmidtke, Peter, Fechner, Nikolas, Simm, Jaak, Arany, Adam, Drizard, Nicolas, Jabal, Rama, Afanasyeva, Arina, Loeb, Regis, Verma, Shlok, Harnqvist, Simon, Holmes, Matthew, Pejo, Balazs, Telenczuk, Maria, Holway, Nicholas, Dieckmann, Arne, Rieke, Nicola, Zumsande, Friederike, Clevert, Djork-Arne, Krug, Michael, Luscombe, Christopher, Green, Darren, Ertl, Peter, Antal, Peter, Marcus, David, Do Huu, Nicolas, Fuji, Hideyoshi, Pickett, Stephen, Acs, Gergely, Boniface, Eric, Beck, Bernd, Sun, Yax, Gohier, Arnaud, Rippmann, Friedrich, Engkvist, Ola, Goeller, Andreas H, Moreau, Yves, Galtier, Mathieu N, Schuffenhauer, Ansgar, Ceulemans, Hugo

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I Have a DREAM! (DiffeRentially privatE smArt Metering) von Ács, Gergely, Castelluccia, Claude

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Near-Optimal Fingerprinting with Constraints von Gulyás, Gábor György, Acs, Gergely, Castelluccia, Claude

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In Search of Lost Utility: Private Location Data von Lestyán, Szilvia, Ács, Gergely, Biczók, Gergely

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SECURED for Health: Scaling Up Privacy to Enable the Integration of the European Health Data Space von Regazzoni, Francesco, Acs, Gergely, Aszalos, Albert Zoltan, Averingos, Christos, Bakalos, Nikolaos, Berral, Josep L, Bos, Joppe W, Brohet, Marco, Castillo Sanz, Andres G, Davies, Gareth T, Florescu, Stefanos, Flory, Pierre-Elisee, Gutierrez-Torre, Alberto, Haleplidis, Evangelos, Heliou, Alice, Ioannidis, Sotirios, El-Kady, Alexander Islam, Kapusta, Katarzyna, Karagianni, Konstantina, Kruizinga, Pieter, Maat, Kyrian, Mann, Zoltan Adam, Mastoraki, Kalliopi, Moon, SeoJeong, Nisevic, Maja, Pejo, Balazs, Papagiannopoulos, Kostas, Paliuras, Vassilis, Palmieri, Paolo, Palumbo, Francesca, Perez Baun, Juan Carlos, Pollner, Peter, Porta-Pardo, Eduard, Pulina, Luca, Siddiqi, Muhammed Ali, Spajic, Daniela, Strydis, Christos, Tasopoulos, Georgios, Thouvenot, Vincent, Tselios, Christos, Fournaris, Apostolos P

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Collaborative Drug Discovery: Inference-level Data Protection Perspective von Pejo, Balazs, Remeli, Mina, Arany, Adam, Galtier, Mathieu, Acs, Gergely

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Provable security of on-demand distance vector routing in wireless ad hoc networks von ACS, Gergely, BUTTYAN, Levente, VAJDA, Istvan

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Automatic Driver Identification from In-Vehicle Network Logs von Remeli, Mina, Lestyan, Szilvia, Acs, Gergely, Biczok, Gergely

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Extracting vehicle sensor signals from CAN logs for driver re-identification von Lestyan, Szilvia, Acs, Gergely, Biczok, Gergely, Szalay, Zsolt

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Privacy-Preserving Release of Spatio-Temporal Density von Acs, Gergely, Biczók, Gergely, Castelluccia, Claude

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Collaborative Drug Discovery: Inference-level Data Protection Perspective von Pejo, Balazs, Remeli, Mina, Arany, Adam, Galtier, Mathieu, Acs, Gergely

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Differentially Private Mixture of Generative Neural Networks von Acs, Gergely, Melis, Luca, Castelluccia, Claude, De Cristofaro, Emiliano

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DREAM: DiffeRentially privatE smArt Metering von Acs, Gergely, Castelluccia, Claude

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