Daniel Jiwoong Im

Cited by

	All	Since 2016
Citations	571	563
h-index	8	8
i10-index	8	8

140

105

20152016201720182019202020212 35 58 131 123 123 87

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 AhnAssistant Professor, ComSci & CogSci, Rutgers UniversityVerified email at rutgers.edu
Jiatao GuFacebook AI ResearchVerified email at fb.com
Mohamed Ishmael BelghaziMontreal Institute for Learning AlgorithmsVerified email at mila.quebec
Nakul VermaColumbia UniversityVerified email at cs.columbia.edu
Gavin Weiguang DingEcopia AIVerified email at uoguelph.ca
Ethan BuchmanUniversity of GuelphVerified email at uoguelph.ca
Jinyao YanPostdoc, Stanford UniversityVerified email at stanford.edu
Sridhama PrakhyaUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Yibo JiangPhD, University of ChicagoVerified email at uchicago.edu
Srinivas C. TuragaHHMI Janelia Research CampusVerified email at janelia.hhmi.org
Cristina SavinNYUVerified email at nyu.edu
Kyunghyun ChoNew York UniversityVerified email at nyu.edu

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	207	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	118	2017
Quantitatively evaluating GANs with divergences proposed for training DJ Im, H Ma, G Taylor, K Branson arXiv preprint arXiv:1803.01045, 2018	69	2018
Neural machine translation with gumbel-greedy decoding J Gu, DJ Im, VOK Li Thirty-Second AAAI Conference on Artificial Intelligence, 2018	35	2018
An empirical analysis of deep network loss surfaces DJ Im, M Tao, K Branson	35	2016
Generative adversarial parallelization DJ Im, H Ma, CD Kim, G Taylor arXiv preprint arXiv:1612.04021, 2016	30	2016
An empirical analysis of the optimization of deep network loss surfaces DJ Im, M Tao, K Branson arXiv preprint arXiv:1612.04010, 2016	21	2016
Semisupervised hyperspectral image classification via neighborhood graph learning DJ Im, GW Taylor IEEE Geoscience and Remote Sensing Letters 12 (9), 1913-1917, 2015	15	2015
Conservativeness of untied auto-encoders DJ Im, MI Belghazi, R Memisevic Thirtieth AAAI Conference on Artificial Intelligence, 2016	8	2016
Stochastic neighbor embedding under f-divergences DJ Im, N Verma, K Branson arXiv preprint arXiv:1811.01247, 2018	7	2018
Neural network regularization via robust weight factorization J Rudy, W Ding, DJ Im, GW Taylor arXiv preprint arXiv:1412.6630, 2014	7	2014
Generative adversarial metric DJ Im, CD Kim, H Jiang, R Memisevic	6	2016
Learning a metric for class-conditional KNN DJ Im, GW Taylor 2016 International Joint Conference on Neural Networks (IJCNN), 1932-1939, 2016	4	2016
Generating images with recurrent adversarial networks. 2016 DJ Im, CD Kim, H Jiang, R Memisevic arXiv preprint arXiv:1602.05110, 0	4
Scoring and classifying with Gated auto-encoders DJ Im, GW Taylor Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015	2	2015
Model-Agnostic Meta-Learning using Runge-Kutta Methods DJ Im, Y Jiang, N Verma arXiv preprint arXiv:1910.07368, 2019	1	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	1	2019
Understanding minimum probability flow for RBMs under various kinds of dynamics DJ Im, E Buchman, GW Taylor arXiv preprint arXiv:1412.6617, 2014	1	2014
Online hyperparameter optimization by real-time recurrent learning DJ Im, C Savin, K Cho arXiv preprint arXiv:2102.07813, 2021		2021
Evaluation metrics for behaviour modeling DJ Im, I Kwak, K Branson arXiv preprint arXiv:2007.12298, 2020		2020

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