Daniel Jiwoong Im
Daniel Jiwoong Im
AIFounded
Verified email at aifounded.com - Homepage
TitleCited byYear
Generating images with recurrent adversarial networks
DJ Im, CD Kim, H Jiang, R Memisevic
arXiv preprint arXiv:1602.05110, 2016
1432016
Denoising criterion for variational auto-encoding framework
DIJ Im, S Ahn, R Memisevic, Y Bengio
Thirty-First AAAI Conference on Artificial Intelligence, 2017
432017
Quantitatively evaluating GANs with divergences proposed for training
DJ Im, H Ma, G Taylor, K Branson
arXiv preprint arXiv:1803.01045, 2018
252018
An empirical analysis of deep network loss surfaces
DJ Im, M Tao, K Branson
212016
Generative adversarial parallelization
DJ Im, H Ma, CD Kim, G Taylor
arXiv preprint arXiv:1612.04021, 2016
192016
Neural machine translation with gumbel-greedy decoding
J Gu, DJ Im, VOK Li
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
92018
An empirical analysis of the optimization of deep network loss surfaces
DJ Im, M Tao, K Branson
arXiv preprint arXiv:1612.04010, 2016
82016
Semisupervised hyperspectral image classification via neighborhood graph learning
DJ Im, GW Taylor
IEEE Geoscience and Remote Sensing Letters 12 (9), 1913-1917, 2015
82015
Neural network regularization via robust weight factorization
J Rudy, W Ding, DJ Im, GW Taylor
arXiv preprint arXiv:1412.6630, 2014
62014
Conservativeness of untied auto-encoders
DJ Im, MI Belghazi, R Memisevic
Thirtieth AAAI Conference on Artificial Intelligence, 2016
52016
Generative adversarial metric
DJ Im, CD Kim, H Jiang, R Memisevic
42016
Learning a metric for class-conditional KNN
DJ Im, GW Taylor
2016 International Joint Conference on Neural Networks (IJCNN), 1932-1939, 2016
22016
Stochastic Neighbor Embedding under f-divergences
DJ Im, N Verma, K Branson
arXiv preprint arXiv:1811.01247, 2018
12018
Understanding minimum probability flow for RBMs under various kinds of dynamics
DJ Im, E Buchman, GW Taylor
arXiv preprint arXiv:1412.6617, 2014
12014
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
2019
An empirical investigation of minimum probability flow learning under different connectivity patterns
DJ Im, E Buchman, GW Taylor
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
2015
Scoring and classifying with Gated auto-encoders
DJ Im, GW Taylor
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
2015
Analyzing Unsupervised Representation Learning Models Under the View of Dynamical Systems
J Im
2015
Improving semi-supervised neural networks for scene understanding by learning the neighborhood graph
J Im, GW Taylor
IEEE CVPR Workshop on Scene Understanding, 2014
2014
An Empirical Evaluation of the Numerical Techiques on American Put Option Valuation
J Im, K Jackson
2013
The system can't perform the operation now. Try again later.
Articles 1–20