Fine-grain atlases of functional modes for fMRI analysis von Dadi, Kamalaker, Varoquaux, Gaël, Machlouzarides-Shalit, Antonia, Gorgolewski, Krzysztof J., Wassermann, Demian, Thirion, Bertrand, Mensch, Arthur

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Benchmarking functional connectome-based predictive models for resting-state fMRI von Dadi, Kamalaker, Rahim, Mehdi, Abraham, Alexandre, Chyzhyk, Darya, Milham, Michael, Thirion, Bertrand, Varoquaux, Gaël

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Loading and plotting of cortical surface representations in Nilearn von Huntenburg, Julia, Abraham, Alexandre, Loula, João, Liem, Franziskus, Dadi, Kamalaker, Varoquaux, Gaël

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Variability in the analysis of a single neuroimaging dataset by many teams von Botvinik-Nezer, Rotem, Holzmeister, Felix, Camerer, Colin F., Dreber, Anna, Johannesson, Magnus, Kirchler, Michael, Iwanir, Roni, Avesani, Paolo, Baczkowski, Blazej M., Bakst, Leah, Ball, Sheryl, Bault, Nadège, Beaton, Derek, Berkers, Ruud M. W. J., Biswal, Bharat B., Bortolini, Tiago, Bowring, Alexander, Braem, Senne, Brooks, Hayley R., Brudner, Emily G., Calderon, Cristian B., Camilleri, Julia A., Castrellon, Jaime J., Dadi, Kamalaker, Davis, Charles P., Luca, Alberto De, Delgado, Mauricio R., Demetriou, Lysia, Dennison, Jeffrey B., Dickie, Erin W., Dobryakova, Ekaterina, Dukart, Juergen, Duncan, Niall W., Fricke, G. Matthew, Fu, Shiguang, Genon, Sarah, Glatard, Tristan, Golowin, Sergej A. E., Gorgolewski, Krzysztof J., Guassi Moreira, João F., Harry, Bronson B., Herholz, Peer, Herman, Gabrielle, Hoffstaedter, Felix, Huettel, Scott A., Hughes, Matthew E., Iordan, Alexandru D., Isager, Peder M., Isik, Ayse I., Joseph, Michael J. E., Juliano, Anthony C., Kassinopoulos, Michalis, Koba, Cemal, Koscik, Timothy R., Kuhl, Brice A., Lauharatanahirun, Nina, Lee, Hongmi, Leemans, Alexander, Li, Monica Y. C., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Mack, Michael L., Malpica, Norberto, Melero, Helena, Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Nilsonne, Gustav, Notter, Michael P., Onicas, Adrian I., Papale, Paolo, Pérez, Alexandre, Pischedda, Doris, Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Schlichting, Margaret L., Sheridan, Margaret A., Skagerlund, Kenny, Smith, Alec, Sokol-Hessner, Peter, Tashjian, Sarah M., Tisdall, Loreen, Tozzi, Leonardo, Turella, Luca, Vijayarajah, Sagana, Weeda, Wouter D., White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Zhang, Lei, Zhang, Xu, Zosky, Joshua E., Nichols, Thomas E., Poldrack, Russell A., Schonberg, Tom

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Population modeling with machine learning can enhance measures of mental health von Dadi, Kamalaker, Varoquaux, Gaël, Houenou, Josselin, Bzdok, Danilo, Thirion, Bertrand, Engemann, Denis

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Machine Learning on Population Imaging for Mental Health von Dadi, Kamalaker

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Big Data in Cognitive Neuroscience: Opportunities and Challenges von Dadi, Kamalaker, Surampudi, Bapi Raju

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Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging von Hebling Vieira, Bruno, Liem, Franziskus, Dadi, Kamalaker, Engemann, Denis A, Gramfort, Alexandre, Bellec, Pierre, Craddock, Richard Cameron, Damoiseaux, Jessica S, Steele, Christopher J, Yarkoni, Tal, Langer, Nicolas, Margulies, Daniel S, Varoquaux, Gael

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Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging von Hebling Vieira, Bruno, Liem, Franziskus, Dadi, Kamalaker, Engemann, Denis A., Gramfort, Alexandre, Bellec, Pierre, Craddock, Richard Cameron, Damoiseaux, Jessica S., Steele, Christopher J., Yarkoni, Tal, Langer, Nicolas, Margulies, Daniel S., Varoquaux, Gaël

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Brainhack: Developing a culture of open, inclusive, community-driven neuroscience von Gau, Rémi, Noble, Stephanie, Heuer, Katja, Bottenhorn, Katherine L., Bilgin, Isil P., Yang, Yu-Fang, Rhoads, Shawn A., Vogelbacher, Christoph, Borghesani, Valentina, Van Den Bossche, Sofie, Kobeleva, Xenia, Atay, Selim Melvin, Varoquaux, Gael P., Huijser, Dorien C., Nastase, Samuel A., Dumas, Guillaume, Moia, Stefano, Brooks, Paula P., Xie, Xihe, Poggiali, Davide, Friedrich, Patrick, Riedl, Lydia, Toro, Roberto, Eklund, Anders, Barrios, Fernando A., Merchant, Junaid S., Oostenveld, Robert, Craddock, R. Cameron, Rokem, Ariel, Doyle, Andrew, Bachar, Dipankar, Bannier, Elise, Basanisi, Ruggero, Basavaraj, Arshitha, Bedini, Marco, Benn, R. Austin, Bradley, Claire, Brown, Jesse, Callahan, Patrick, Cheng, Theresa, Chopra, Sidhant, Close, Thomas G., Cona, Giorgia, Cury, Claire, Dadi, Kamalaker, Das, Samir, De Vico Fallani, Fabrizio, Duff, Eugene P., Dziura, Sarah, Esteban, Oscar, Flannery, Jessica E., Flournoy, John, Forkel, Stephanie J., Franco, Alexandre R., García Alanis, José C., Garyfallidis, Eleftherios, Hayot-Sasson, Valérie, Hohmann, Daniela M., Iordan, Alexandru, Jiang, Chao, Joseph, Michael, Kennedy, David N., Keshavan, Anisha, Khan, Ali R., Kiar, Gregory, Koppelmans, Vincent, Langs, Georg, Laws, Marissa, Licandro, Roxane, Liew, Sook-Lei, Litinas, Krisanne, Lussier, Désirée, Mansour L, Sina, Manzano-Patron, J.P., Margulies, Daniel S., Marinato, Giorgio, Markiewicz, Christopher J., Meunier, David, Milham, Michael P., Momi, Davide, Moreau, Clara A., Nielson, Dylan M., Park, Patrick J., Pasquini, Lorenzo, Pienaar, Rudolph, Qiu, Anqi, Scharinger, Mathias, Shaw, Thomas B., Simmonite, Molly, Spence, Hayli, Stajduhar, Andrija, Szinte, Martin, Tam, Angela, Thiebaut de Schotten, Michel, Tomaz da Silva, Laura, Vallesi, Antonino, Vukojević, Jakša, Wideman, Steve, Xie, Hua, Zuo, Xi-Nian

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Population modeling with machine learning can enhance measures of mental health von Dadi, Kamalaker, Varoquaux, Gaël, Houenou, Josselin, Bzdok, Danilo, Thirion, Bertrand, Engemann, Denis

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mulEEG: A Multi-view Representation Learning on EEG Signals von Kumar, Vamsi, Reddy, Likith, Kumar Sharma, Shivam, Dadi, Kamalaker, Yarra, Chiranjeevi, Bapi, Raju S., Rajendran, Srijithesh

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BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision von Deb, Prantik, Baru, Lalith Bharadwaj, Dadi, Kamalaker, S, Bapi Raju

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HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable Hyperedges von Arora, Mehul, Jain, Chirag Shantilal, Lalith Bharadwaj Baru, Dadi, Kamalaker, Bapi Raju Surampudi

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BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision von Prantik Deb, Lalith Bharadwaj Baru, Dadi, Kamalaker, Bapi, Raju S

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Fine-grain atlases of functional modes for fMRI analysis von Dadi, Kamalaker, Varoquaux, Gaël, Machlouzarides-Shalit, Antonia, Gorgolewski, Krzysztof J, Wassermann, Demian, Thirion, Bertrand, Mensch, Arthur

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Supporting data for "Population modeling with machine learning can enhance measures of mental health" von Kamalaker, Dadi, Gaël, Varoquaux, Josselin, Houenou, Danilo, Bzdok, Bertrand, Thirion, Denis, Engemann

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Fine-grain atlases of functional modes for fMRI analysis von Dadi, Kamalaker, Varoquaux, Gaël, Machlouzarides-Shalit, Antonia, Gorgolewski, Krzysztof J, Wassermann, Demian, Thirion, Bertrand, Mensch, Arthur

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