Daniel Jiwoong Im | DeepAI

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∙ 08/18/2023

Active and Passive Causal Inference Learning

This paper serves as a starting point for machine learning researchers, ...

0 Daniel Jiwoong Im, et al. ∙

∙ 08/11/2023

UAMM: UBET Automated Market Maker

Automated market makers (AMMs) are pricing mechanisms utilized by decent...

0 Daniel Jiwoong Im, et al. ∙

∙ 02/15/2021

Online hyperparameter optimization by real-time recurrent learning

Conventional hyperparameter optimization methods are computationally int...

4 Daniel Jiwoong Im, et al. ∙

∙ 07/23/2020

Evaluation metrics for behaviour modeling

A primary difficulty with unsupervised discovery of structure in large d...

6 Daniel Jiwoong Im, et al. ∙

∙ 12/04/2019

Are skip connections necessary for biologically plausible learning rules?

Backpropagation is the workhorse of deep learning, however, several othe...

0 Daniel Jiwoong Im, et al. ∙

∙ 10/16/2019

Model-Agnostic Meta-Learning using Runge-Kutta Methods

Meta-learning has emerged as an important framework for learning new tas...

0 Daniel Jiwoong Im, et al. ∙

∙ 06/07/2019

Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data

The Importance Weighted Auto Encoder (IWAE) objective has been shown to ...

0 Daniel Jiwoong Im, et al. ∙

∙ 11/03/2018

Stochastic Neighbor Embedding under f-divergences

The t-distributed Stochastic Neighbor Embedding (t-SNE) is a powerful an...

0 Daniel Jiwoong Im, et al. ∙

∙ 03/02/2018

Quantitatively Evaluating GANs With Divergences Proposed for Training

Generative adversarial networks (GANs) have been extremely effective in ...

0 Daniel Jiwoong Im, et al. ∙

∙ 06/22/2017

Neural Machine Translation with Gumbel-Greedy Decoding

Previous neural machine translation models used some heuristic search al...

0 Jiatao Gu, et al. ∙

∙ 07/11/2016

Learning a metric for class-conditional KNN

Naive Bayes Nearest Neighbour (NBNN) is a simple and effective framework...

0 Daniel Jiwoong Im, et al. ∙

∙ 02/16/2016

Generating images with recurrent adversarial networks

Gatys et al. (2015) showed that optimizing pixels to match features in a...

0 Daniel Jiwoong Im, et al. ∙

∙ 12/20/2014

Neural Network Regularization via Robust Weight Factorization

Regularization is essential when training large neural networks. As deep...

0 Jan Rudy, et al. ∙

∙ 12/20/2014

Scoring and Classifying with Gated Auto-encoders

Auto-encoders are perhaps the best-known non-probabilistic methods for r...

0 Daniel Jiwoong Im, et al. ∙

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