Neural Network Regularization via Robust Weight Factorization. - Jan Rudy; Weiguang Ding; Daniel Jiwoong Im; Graham W. Taylor (CoRR, 2014)

An Empirical Investigation of Minimum Probability Flow Learning Under Different Connectivity Patterns. - Daniel Jiwoong Im; Ethan Buchman; Graham W. Taylor (ECML/PKDD (1), 2015)

Scoring and Classifying with Gated Auto-Encoders. - Daniel Jiwoong Im; Graham W. Taylor (ECML/PKDD (1), 2015)

Understanding Minimum Probability Flow for RBMs Under Various Kinds of Dynamics. - Daniel Jiwoong Im; Ethan Buchman; Graham W. Taylor (ICLR (Workshop), 2015)

Semisupervised Hyperspectral Image Classification via Neighborhood Graph Learning. - Daniel Jiwoong Im; Graham W. Taylor (IEEE Geosci. Remote. Sens. Lett., 2015)

Conservativeness of Untied Auto-Encoders. - Daniel Jiwoong Im; Mohamed Ishmael Diwan Belghazi; Roland Memisevic (AAAI, 2016)

Learning a metric for class-conditional KNN. - Daniel Jiwoong Im; Graham W. Taylor (IJCNN, 2016)

Generating images with recurrent adversarial networks. - Daniel Jiwoong Im; Chris Dongjoo Kim; Hui Jiang; Roland Memisevic (CoRR, 2016)

Generative Adversarial Parallelization. - Daniel Jiwoong Im; He Ma; Chris Dongjoo Kim; Graham W. Taylor (CoRR, 2016)

An Empirical Analysis of Deep Network Loss Surfaces. - Daniel Jiwoong Im; Michael Tao 001; Kristin Branson (CoRR, 2016)

Denoising Criterion for Variational Auto-Encoding Framework. - Daniel Jiwoong Im; Sungjin Ahn; Roland Memisevic; Yoshua Bengio (AAAI, 2017)

Neural Machine Translation with Gumbel-Greedy Decoding. - Jiatao Gu; Daniel Jiwoong Im; Victor O. K. Li (AAAI, 2018)

Quantitatively Evaluating GANs With Divergences Proposed for Training. - Daniel Jiwoong Im; He Ma; Graham W. Taylor; Kristin Branson (ICLR (Poster), 2018)

Stochastic Neighbor Embedding under f-divergences. - Daniel Jiwoong Im; Nakul Verma; Kristin Branson (CoRR, 2018)

Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data. - Daniel Jiwoong Im; Sridhama Prakhya; Jinyao Yan; Srinivas C. Turaga; Kristin Branson (CoRR, 2019)

Model-Agnostic Meta-Learning using Runge-Kutta Methods. - Daniel Jiwoong Im; Yibo Jiang; Nakul Verma (CoRR, 2019)

Are skip connections necessary for biologically plausible learning rules? - Daniel Jiwoong Im; Rutuja Patil; Kristin Branson (CoRR, 2020)

Evaluation metrics for behaviour modeling. - Daniel Jiwoong Im; Iljung S. Kwak; Kristin Branson (CoRR, 2020)

Online hyperparameter optimization by real-time recurrent learning. - Daniel Jiwoong Im; Cristina Savin; Kyunghyun Cho (CoRR, 2021)

Causal Effect Variational Autoencoder with Uniform Treatment. - Daniel Jiwoong Im; Kyunghyun Cho; Narges Razavian (CoRR, 2021)

UAMM: UBET Automated Market Maker. - Daniel Jiwoong Im; Alexander Kondratskiy; Vincent Harvey; Hsuan-Wei Fu (CoRR, 2023)

Active and Passive Causal Inference Learning. - Daniel Jiwoong Im; Kyunghyun Cho (CoRR, 2023)

Onchain Sports Betting using UBET Automated Market Maker. - Daniel Jiwoong Im; Alexander Kondratskiy; Vincent Harvey; Hsuan-Wei Fu (CoRR, 2023)

Using Deep Autoregressive Models as Causal Inference Engines. - Daniel Jiwoong Im; Kevin Zhang; Nakul Verma; Kyunghyun Cho (CoRR, 2024)

Deep Autoregressive Models as Causal Inference Engines. - Daniel Jiwoong Im; Kevin Zhang; Nakul Verma; Kyunghyun Cho (Trans. Mach. Learn. Res., 2025)