20 citations · 21 across the 4 of their papers we have counts for
7 papers
Evaluation metrics for behaviour modeling
Daniel Jiwoong Im, Iljung Kwak, Kristin Branson
A primary difficulty with unsupervised discovery of structure in large data sets is a lack of quantitative evaluation criteria. In this work, we propose and investigate several met…
Are skip connections necessary for biologically plausible learning rules?
Daniel Jiwoong Im, Rutuja Patil, Kristin Branson
Backpropagation is the workhorse of deep learning, however, several other biologically-motivated learning rules have been introduced, such as random feedback alignment and differen…
Detecting the Starting Frame of Actions in Video
Iljung S. Kwak, Jian-Zhong Guo, Adam Hantman +2
In this work, we address the problem of precisely localizing key frames of an action, for example, the precise time that a pitcher releases a baseball, or the precise time that a c…
Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data
Daniel Jiwoong Im, Sridhama Prakhya, Jinyao Yan +2
The Importance Weighted Auto Encoder (IWAE) objective has been shown to improve the training of generative models over the standard Variational Auto Encoder (VAE) objective. Here,…
Stochastic Neighbor Embedding under f-divergences
Daniel Jiwoong Im, Nakul Verma, Kristin Branson
The t-distributed Stochastic Neighbor Embedding (t-SNE) is a powerful and popular method for visualizing high-dimensional data. It minimizes the Kullback-Leibler (KL) divergence be…
Network-size independent covering number bounds for deep networks
Mayank Kabra, Kristin Branson
We give a covering number bound for deep learning networks that is independent of the size of the network. The key for the simple analysis is that for linear classifiers, rotating…