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Maddie Cusimano
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2020 – today
- 2023
- [c5]Masato Hagiwara, Benjamin Hoffman, Jen-Yu Liu, Maddie Cusimano, Felix Effenberger, Katie Zacarian:
BEANS: The Benchmark of Animal Sounds. ICASSP 2023: 1-5 - [i4]Benjamin Hoffman, Maddie Cusimano, Vittorio Baglione, Daniela Canestrari, Damien Chevallier, Dominic L. DeSantis, Lorène Jeantet, Monique A. Ladds, Takuya Maekawa, Vicente Mata-Silva, Víctor Moreno-González, Eva Trapote, Outi Vainio, Antti Vehkaoja, Ken Yoda, Katherine Zacarian
, Ari Friedlaender, Christian Rutz:
A benchmark for computational analysis of animal behavior, using animal-borne tags. CoRR abs/2305.10740 (2023) - 2022
- [c4]Sean Dae Houlihan, Desmond C. Ong, Maddie Cusimano, Rebecca Saxe:
Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. CogSci 2022 - [i3]Masato Hagiwara, Maddie Cusimano, Jen-Yu Liu:
Modeling Animal Vocalizations through Synthesizers. CoRR abs/2210.10857 (2022) - [i2]Masato Hagiwara, Benjamin Hoffman, Jen-Yu Liu, Maddie Cusimano, Felix Effenberger, Katie Zacarian
BEANS: The Benchmark of Animal Sounds. CoRR abs/2210.12300 (2022) - 2021
- [c3]Vinayak Agarwal
Object-Based Synthesis of Scraping and Rolling Sounds Based on Non-Linear Physical Constraints. DAFx 2021: 136-143 - [i1]Vinayak Agarwal, Maddie Cusimano, James Traer, Josh H. McDermott:
Object-based synthesis of scraping and rolling sounds based on non-linear physical constraints. CoRR abs/2112.08984 (2021)
2010 – 2019
- 2019
- [c2]Maddie Cusimano, Josh H. McDermott:
Scrape, rub, and roll: causal inference in the perception of sustained contact sounds. CogSci 2019: 3437 - 2018
- [c1]Maddie Cusimano, Luke B. Hewitt, Josh Tenenbaum, Josh H. McDermott:
Auditory scene analysis as Bayesian inference in sound source models. CogSci 2018
Coauthor Index
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