Cinjon Resnick
Cinjon Resnick
PhD Student, NYU
Verified email at
Cited by
Cited by
Neural audio synthesis of musical notes with wavenet autoencoders
J Engel, C Resnick, A Roberts, S Dieleman, M Norouzi, D Eck, ...
International Conference on Machine Learning, 1068-1077, 2017
Pommerman: A multi-agent playground
C Resnick, W Eldridge, D Ha, D Britz, J Foerster, J Togelius, K Cho, ...
arXiv preprint arXiv:1809.07124, 2018
Capacity, bandwidth, and compositionality in emergent language learning
C Resnick, A Gupta, J Foerster, AM Dai, K Cho
Proc. of the 19th International Conference on Autonomous Agents and …, 2019
Backplay:" man muss immer umkehren"
C Resnick, R Raileanu, S Kapoor, A Peysakhovich, K Cho, J Bruna
arXiv preprint arXiv:1807.06919, 2018
Generating music with deep neural networks
J Engel, M Norouzi, K Simonyan, A Roberts, C Resnick, SEL Dieleman, ...
US Patent 10,068,557, 2018
Ridge rider: Finding diverse solutions by following eigenvectors of the hessian
J Parker-Holder, L Metz, C Resnick, H Hu, A Lerer, A Letcher, ...
Advances in Neural Information Processing Systems 33, 753-765, 2020
Audio Deepdream: Optimizing raw audio with convolutional networks
D Ardila, C Resnick, A Roberts, D Eck
Interactive musical improvisation with Magenta
A Roberts, J Engel, C Hawthorne, I Simon, E Waite, S Oore, N Jaques, ...
Proc. NIPS, 2016
Multi-agent path finding for precedence-constrained goal sequences
H Zhang, J Chen, J Li, B Williams, S Koenig
International Joint Conference on Autonomous Agents and Multiagent Systems …, 2022
Vehicle communication strategies for simulated highway driving
C Resnick, I Kulikov, K Cho, J Weston
Proceedings of the 1st Workshop on Emergent Communication, NIPS 2017, 2018
Compositionality and capacity in emergent languages
A Gupta, C Resnick, J Foerster, A Dai, K Cho
Proceedings of the 5th Workshop on Representation Learning for NLP, 34-38, 2020
Probing the state of the art: A critical look at visual representation evaluation
C Resnick, Z Zhan, J Bruna
arXiv preprint arXiv:1912.00215, 2019
In-distribution interpretability for challenging modalities
C Heiß, R Levie, C Resnick, G Kutyniok, J Bruna
arXiv preprint arXiv:2007.00758, 2020
Causal Scene BERT: Improving object detection by searching for challenging groups of data
C Resnick, O Litany, A Kar, K Kreis, J Lucas, K Cho, S Fidler
arXiv preprint arXiv:2202.03651, 2022
Pommerman & NeurIPS 2018: Multi-Agent Competition
C Resnick, C Gao, G Márton, T Osogami, L Pang, T Takahashi
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders, 2017
J Engel, C Resnick, A Roberts, S Dieleman, D Eck, K Simonyan, ...
Google Scholar Google Scholar Digital Library Digital Library, 2017
Model ai assignments 2019
TW Neller, R Sooriamurthi, M Guerzhoy, L Zhang, P Talaga, C Archibald, ...
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9751-9753, 2019
Model AI Assignments 2020
TW Neller, S Keeley, M Guerzhoy, W Hoenig, J Li, S Koenig, A Soni, ...
Proceedings of the AAAI conference on artificial intelligence 34 (09), 13509 …, 2020
Depth First Learning: Learning to Understand Machine Learning
A Oliver, S Bhupatiraju, C Resnick, KK Agrawal
Identifying, Addressing, and Understanding Challenging Cases in Machine Learning
C Resnick
New York University, 2022
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