Jul 30 2019
Breaking Deep Neural Networks with Adversarial Attacks
Jul 30 2019
Analyzing different adversarial attacks, their effects on the representation space and potential defense mechanisms.
Apr 24 2019
Deep Clustering: Using Deep Neural Networks for Clustering
Apr 24 2019
A comprehensive introduction and discussion of recent works on dee learning based clustering algorithms.
Jun 02 2017
Gradient Descent, Momentum and Adaptive Learning Rate
Jun 02 2017
Implementing momentum and adaptive learning rate, the core ideas behind the most popular gradient descent variants.
Jun 02 2017
Softmax and Cross Entropy Loss
Jun 02 2017
Understanding the intuition and maths behind softmax and the cross entropy loss - the ubiquitous combination in classification algorithms.
May 17 2017
Batch Normalization: Stabilizing Deep Neural Network Training
May 17 2017
Deriving batch normalization and gradients from scratch.
May 12 2017
Maxpooling: Summarizing the Spatial Information
May 12 2017
Pooling layers are important downsamplers that summarize the activations and keep the number of network parameters low.
May 07 2017
Convolution: The core idea behind CNNs
May 07 2017
Understanding convolutional layers and their cryptic implementation in CNNs.
