Cassiano Becker

出版物

表示方法:

- Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting
  
  Emmanuel Aboah Boateng, Cassiano Becker, Nabiha Asghar, Kabir Walia, Ashwin Srinivasan, Ehi Nosakhare, Soundararajan Srinivasan, Victor Dibia
  
  Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track) | April 2025
  
  Publication
- Node Similarities under Random Projections: Limits and Pathological Cases
  
  Tvrtko Tadić, Cassiano Becker, Jennifer Neville
  
  International Conference on Learning Representations (ICLR) | April 2025
  
  Preprint Publication
- Rethinking Node Representation Interpretation through Relation Coherence
  
  Ying-Chun Lin, Jennifer Neville, Cassiano Becker, Purvanshi Metha, Nabiha Asghar, Vipul Agarwal
  
  September 2024
  
  Publication
- Models of communication and control for brain networks: distinctions, convergence, and future outlook
  
  P. Srivastava, Erfan Nozari, Jason Z. Kim, Harang Ju, D. Zhou, Cassiano Becker, F. Pasqualetti, George Pappas, D. Bassett
  
  Network Neuroscience | December 2019, 巻4: pp. 1122-1159
  
  DOI Publication Publication Publication Publication
- Variational Inference for Linear Systems with Latent Parameter Space
  
  Cassiano Becker, V. Preciado
  
  2019 American Control Conference (ACC) | June 2019, pp. 5662-5667
  
  DOI Publication
- Network Design for Controllability Metrics
  
  Cassiano Becker, S. Pequito, George Pappas, V. Preciado
  
  IEEE Transactions on Control of Network Systems | February 2019, 巻7: pp. 1404-1415
  
  DOI Publication Publication Publication
- Large-scale dynamic modeling of task-fMRI signals via subspace system identification
  
  Cassiano Becker, D. Bassett, V. Preciado
  
  Journal of Neural Engineering | August 2018, 巻15
  
  DOI Publication
- Spectral mapping of brain functional connectivity from diffusion imaging
  
  Cassiano Becker, S. Pequito, George Pappas, Michael B. Miller, Scott T. Grafton, D. Bassett, V. Preciado
  
  Nature Scientific Reports | January 2018, 巻8
  
  DOI Publication Publication Publication

- Models of communication and control for brain networks: distinctions, convergence, and future outlook
  
  P. Srivastava, Erfan Nozari, Jason Z. Kim, Harang Ju, D. Zhou, Cassiano Becker, F. Pasqualetti, George Pappas, D. Bassett
  
  Network Neuroscience | December 2019, 巻4: pp. 1122-1159
  
  DOI Publication Publication Publication Publication
- Large-scale dynamic modeling of task-fMRI signals via subspace system identification
  
  Cassiano Becker, D. Bassett, V. Preciado
  
  Journal of Neural Engineering | August 2018, 巻15
  
  DOI Publication
- Spectral mapping of brain functional connectivity from diffusion imaging
  
  Cassiano Becker, S. Pequito, George Pappas, Michael B. Miller, Scott T. Grafton, D. Bassett, V. Preciado
  
  Nature Scientific Reports | January 2018, 巻8
  
  DOI Publication Publication Publication
- Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting
  
  Emmanuel Aboah Boateng, Cassiano Becker, Nabiha Asghar, Kabir Walia, Ashwin Srinivasan, Ehi Nosakhare, Soundararajan Srinivasan, Victor Dibia
  
  Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track) | April 2025
  
  Publication
- Node Similarities under Random Projections: Limits and Pathological Cases
  
  Tvrtko Tadić, Cassiano Becker, Jennifer Neville
  
  International Conference on Learning Representations (ICLR) | April 2025
  
  Preprint Publication
- Rethinking Node Representation Interpretation through Relation Coherence
  
  Ying-Chun Lin, Jennifer Neville, Cassiano Becker, Purvanshi Metha, Nabiha Asghar, Vipul Agarwal
  
  September 2024
  
  Publication
- Variational Inference for Linear Systems with Latent Parameter Space
  
  Cassiano Becker, V. Preciado
  
  2019 American Control Conference (ACC) | June 2019, pp. 5662-5667
  
  DOI Publication
- Large-scale dynamic modeling of task-fMRI signals via subspace system identification
  
  Cassiano Becker, D. Bassett, V. Preciado
  
  Journal of Neural Engineering | August 2018, 巻15
  
  DOI Publication
- Network Design for Controllability Metrics
  
  Cassiano Becker, S. Pequito, George Pappas, V. Preciado
  
  IEEE Transactions on Control of Network Systems | February 2019, 巻7: pp. 1404-1415
  
  DOI Publication Publication Publication
- Spectral mapping of brain functional connectivity from diffusion imaging
  
  Cassiano Becker, S. Pequito, George Pappas, Michael B. Miller, Scott T. Grafton, D. Bassett, V. Preciado
  
  Nature Scientific Reports | January 2018, 巻8
  
  DOI Publication Publication Publication
- Node Similarities under Random Projections: Limits and Pathological Cases
  
  Tvrtko Tadić, Cassiano Becker, Jennifer Neville
  
  International Conference on Learning Representations (ICLR) | April 2025
  
  Preprint Publication
- Network Design for Controllability Metrics
  
  Cassiano Becker, S. Pequito, George Pappas, V. Preciado
  
  IEEE Transactions on Control of Network Systems | February 2019, 巻7: pp. 1404-1415
  
  DOI Publication Publication Publication
- Rethinking Node Representation Interpretation through Relation Coherence
  
  Ying-Chun Lin, Jennifer Neville, Cassiano Becker, Purvanshi Metha, Nabiha Asghar, Vipul Agarwal
  
  September 2024
  
  Publication
- Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting
  
  Emmanuel Aboah Boateng, Cassiano Becker, Nabiha Asghar, Kabir Walia, Ashwin Srinivasan, Ehi Nosakhare, Soundararajan Srinivasan, Victor Dibia
  
  Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track) | April 2025
  
  Publication

- Models of communication and control for brain networks: distinctions, convergence, and future outlook
  
  P. Srivastava, Erfan Nozari, Jason Z. Kim, Harang Ju, D. Zhou, Cassiano Becker, F. Pasqualetti, George Pappas, D. Bassett
  
  Network Neuroscience | December 2019, 巻4: pp. 1122-1159
  
  DOI Publication Publication Publication Publication
- Variational Inference for Linear Systems with Latent Parameter Space
  
  Cassiano Becker, V. Preciado
  
  2019 American Control Conference (ACC) | June 2019, pp. 5662-5667
  
  DOI Publication
- Network Design for Controllability Metrics
  
  Cassiano Becker, S. Pequito, George Pappas, V. Preciado
  
  IEEE Transactions on Control of Network Systems | February 2019, 巻7: pp. 1404-1415
  
  DOI Publication Publication Publication
- Large-scale dynamic modeling of task-fMRI signals via subspace system identification
  
  Cassiano Becker, D. Bassett, V. Preciado
  
  Journal of Neural Engineering | August 2018, 巻15
  
  DOI Publication
- Spectral mapping of brain functional connectivity from diffusion imaging
  
  Cassiano Becker, S. Pequito, George Pappas, Michael B. Miller, Scott T. Grafton, D. Bassett, V. Preciado
  
  Nature Scientific Reports | January 2018, 巻8
  
  DOI Publication Publication Publication
- Rethinking Node Representation Interpretation through Relation Coherence
  
  Ying-Chun Lin, Jennifer Neville, Cassiano Becker, Purvanshi Metha, Nabiha Asghar, Vipul Agarwal
  
  September 2024
  
  Publication
- Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting
  
  Emmanuel Aboah Boateng, Cassiano Becker, Nabiha Asghar, Kabir Walia, Ashwin Srinivasan, Ehi Nosakhare, Soundararajan Srinivasan, Victor Dibia
  
  Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track) | April 2025
  
  Publication
- Node Similarities under Random Projections: Limits and Pathological Cases
  
  Tvrtko Tadić, Cassiano Becker, Jennifer Neville
  
  International Conference on Learning Representations (ICLR) | April 2025
  
  Preprint Publication

Cassiano Becker

出版物

Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting

Node Similarities under Random Projections: Limits and Pathological Cases

Rethinking Node Representation Interpretation through Relation Coherence

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Variational Inference for Linear Systems with Latent Parameter Space

Network Design for Controllability Metrics

Large-scale dynamic modeling of task-fMRI signals via subspace system identification

Spectral mapping of brain functional connectivity from diffusion imaging

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Large-scale dynamic modeling of task-fMRI signals via subspace system identification

Spectral mapping of brain functional connectivity from diffusion imaging

Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting

Node Similarities under Random Projections: Limits and Pathological Cases

Rethinking Node Representation Interpretation through Relation Coherence

Variational Inference for Linear Systems with Latent Parameter Space

Large-scale dynamic modeling of task-fMRI signals via subspace system identification

Network Design for Controllability Metrics

Spectral mapping of brain functional connectivity from diffusion imaging

Node Similarities under Random Projections: Limits and Pathological Cases

Network Design for Controllability Metrics

Rethinking Node Representation Interpretation through Relation Coherence

Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Variational Inference for Linear Systems with Latent Parameter Space

Network Design for Controllability Metrics

Large-scale dynamic modeling of task-fMRI signals via subspace system identification

Spectral mapping of brain functional connectivity from diffusion imaging

Rethinking Node Representation Interpretation through Relation Coherence

Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting

Node Similarities under Random Projections: Limits and Pathological Cases