Daniel Jiwoong Im
Daniel Jiwoong Im
AIFounded
Verified email at aifounded.com - Homepage
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
1782016
Denoising criterion for variational auto-encoding framework
DJ Im, S Ahn, R Memisevic, Y Bengio
arXiv preprint arXiv:1511.06406, 2015
882015
Quantitatively evaluating GANs with divergences proposed for training
DJ Im, H Ma, G Taylor, K Branson
arXiv preprint arXiv:1803.01045, 2018
502018
An empirical analysis of deep network loss surfaces
DJ Im, M Tao, K Branson
292016
Neural machine translation with gumbel-greedy decoding
J Gu, DJ Im, VOK Li
arXiv preprint arXiv:1706.07518, 2017
262017
Generative adversarial parallelization
DJ Im, H Ma, CD Kim, G Taylor
arXiv preprint arXiv:1612.04021, 2016
192016
Semisupervised hyperspectral image classification via neighborhood graph learning
DJ Im, GW Taylor
IEEE Geoscience and Remote Sensing Letters 12 (9), 1913-1917, 2015
132015
An empirical analysis of the optimization of deep network loss surfaces
DJ Im, M Tao, K Branson
arXiv preprint arXiv:1612.04010, 2016
122016
Conservativeness of untied auto-encoders
DJ Im, MID Belghazi, R Memisevic
arXiv preprint arXiv:1506.07643, 2015
72015
Neural network regularization via robust weight factorization
J Rudy, W Ding, DJ Im, GW Taylor
arXiv preprint arXiv:1412.6630, 2014
72014
Generative adversarial metric
DJ Im, CD Kim, H Jiang, R Memisevic
52016
Stochastic Neighbor Embedding under f-divergences
DJ Im, N Verma, K Branson
arXiv preprint arXiv:1811.01247, 2018
42018
Learning a metric for class-conditional KNN
DJ Im, GW Taylor
2016 International Joint Conference on Neural Networks (IJCNN), 1932-1939, 2016
32016
Model-Agnostic Meta-Learning using Runge-Kutta Methods
DJ Im, Y Jiang, N Verma
arXiv preprint arXiv:1910.07368, 2019
12019
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
12019
Scoring and classifying with Gated auto-encoders
DJ Im, GW Taylor
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
12015
Understanding minimum probability flow for RBMs under various kinds of dynamics
DJ Im, E Buchman, GW Taylor
arXiv preprint arXiv:1412.6617, 2014
12014
Evaluation metrics for behaviour modeling
DJ Im, I Kwak, K Branson
arXiv preprint arXiv:2007.12298, 2020
2020
Are skip connections necessary for biologically plausible learning rules?
DJ Im, R Patil, K Branson
arXiv preprint arXiv:2001.01647, 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
The system can't perform the operation now. Try again later.
Articles 1–20