Daniel Jiwoong Im

Cited by

	All	Since 2017
Citations	665	625
h-index	9	9
i10-index	9	9

140

105

201520162017201820192020202120222 33 59 135 129 122 127 52

Co-authors

Graham TaylorUniversity of Guelph and Vector Institute for Artificial IntelligenceVerified email at uoguelph.ca
Roland MemisevicTwenty Billion Neurons, University of MontrealVerified email at twentybn.com
Kristin BransonHHMI Janelia Research CampusVerified email at janelia.hhmi.org
Hui JiangProfessor of Electrical Engineering and Computer Science, York UniversityVerified email at cse.yorku.ca
He MaSchool of Engineering, University of GuelphVerified email at uoguelph.ca
Michael TaoUniversity of TorontoVerified email at dgp.toronto.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Sungjin AhnAssociate Professor, KAISTVerified email at kaist.ac.kr
Jiatao GuApple AI/ML (MLR)Verified email at apple.com
Nakul VermaColumbia UniversityVerified email at cs.columbia.edu
Mohamed Ishmael BelghaziMontreal Institute for Learning AlgorithmsVerified email at mila.quebec
Gavin Weiguang DingEcopia AIVerified email at uoguelph.ca
Kyunghyun ChoNew York University, GenentechVerified email at nyu.edu
Ethan BuchmanUniversity of GuelphVerified email at uoguelph.ca
Jinyao YanPostdoc, Janelia Research CampusVerified email at janelia.hhmi.org
Sridhama PrakhyaGoogle Research / University of Massachusetts AmherstVerified email at google.com
Cristina SavinNYUVerified email at nyu.edu
Yibo JiangPhD, University of ChicagoVerified email at uchicago.edu
Srinivas C. TuragaHHMI Janelia Research CampusVerified email at janelia.hhmi.org

Daniel Jiwoong Im

New York University

Verified email at nyu.edu - Homepage

Machine learning Casual Inference Meta Learning Reinforcement Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Generating images with recurrent adversarial networks DJ Im, CD Kim, H Jiang, R Memisevic arXiv preprint arXiv:1602.05110, 2016	228	2016
Denoising criterion for variational auto-encoding framework D Im Im, S Ahn, R Memisevic, Y Bengio Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	147	2017
Quantitatively evaluating GANs with divergences proposed for training DJ Im, H Ma, G Taylor, K Branson arXiv preprint arXiv:1803.01045, 2018	72	2018
An empirical analysis of deep network loss surfaces DJ Im, M Tao, K Branson	38	2016
Neural machine translation with gumbel-greedy decoding J Gu, DJ Im, VOK Li Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	37	2018
Generative adversarial parallelization DJ Im, H Ma, CD Kim, G Taylor arXiv preprint arXiv:1612.04021, 2016	33	2016
An empirical analysis of the optimization of deep network loss surfaces DJ Im, M Tao, K Branson arXiv preprint arXiv:1612.04010, 2016	31	2016
Semisupervised hyperspectral image classification via neighborhood graph learning DJ Im, GW Taylor IEEE Geoscience and Remote Sensing Letters 12 (9), 1913-1917, 2015	16	2015
Stochastic neighbor embedding under f-divergences DJ Im, N Verma, K Branson arXiv preprint arXiv:1811.01247, 2018	10	2018
Neural network regularization via robust weight factorization J Rudy, W Ding, DJ Im, GW Taylor arXiv preprint arXiv:1412.6630, 2014	9	2014
Conservativeness of untied auto-encoders DJ Im, MI Belghazi, R Memisevic Thirtieth AAAI Conference on Artificial Intelligence, 2016	8	2016
Learning a metric for class-conditional KNN DJ Im, GW Taylor 2016 International Joint Conference on Neural Networks (IJCNN), 1932-1939, 2016	6	2016
Generative adversarial metric DJ Im, CD Kim, H Jiang, R Memisevic	5	2016
Generating images with recurrent adversarial networks. arXiv 2016 DJ Im, CD Kim, H Jiang, R Memisevic arXiv preprint arXiv:1602.05110, 0	5
Generating images with recurrent adversarial networks. 2016 DJ Im, CD Kim, H Jiang, R Memisevic arXiv preprint arXiv:1602.05110, 0	5
Online hyperparameter optimization by real-time recurrent learning DJ Im, C Savin, K Cho arXiv preprint arXiv:2102.07813, 2021	3	2021
Model-agnostic meta-learning using runge-kutta methods DJ Im, Y Jiang, N Verma arXiv preprint arXiv:1910.07368, 2019	3	2019
Importance weighted adversarial variational autoencoders for spike inference from calcium imaging data DJ Im, S Prakhya, J Yan, S Turaga, K Branson arXiv preprint arXiv:1906.03214, 2019	3	2019
Scoring and classifying with gated auto-encoders DJ Im, GW Taylor Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015	2	2015
Auto-encoding variational Bayes DJ Im, S Ahn, R Memisevic, Y Bengio CoRR, 2014	2	2014

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