Generative Adversarial Networks, or GANs for short, were first described in the 2014 paper by Ian Goodfellow, et al. titled

Pre-training general-purpose visual features with convolutional neural networks without relying on annotations is a challenging and important task. Most recent efforts in unsupervised feature learning have focused on either small or highly curated datasets…

By Aaron Gokaslan* and Vanya Cohen*

In this work, we present a bidirectional system that can animate avatar heads of both users’ full likeness using consumer-friendly headset mounted cameras (HMC). There are two main challenges in doing this: unaccommodating camera views and the image-to-avatar…

Generative Adversarial Networks, or GANs, are perhaps the most effective generative model for image synthesis.

Nevertheless, they are typically restricted to generating small images and the training process remains fragile, dependent upon specific augmentations…

Facebook AI researchers are releasing a new feature for the fastText library that provides hyperparameter autotuning for more efficient text classifiers.

📝 The paper "Efficient Video Generation on Complex Datasets" is available here:
https://arxiv.org/abs/1907.06571

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Implements the unsupervised pre-training of convolutional neural networks - GitHub - facebookresearch/DeeperCluster: Implements the unsupervised pre-training of convolutional neural networks

The Frechet Inception Distance score, or FID for short, is a metric that calculates the distance between feature vectors calculated for real and generated images. The score summarizes how similar the two groups are in terms of statistics on computer vision…

Adaptive gradient-based optimizers such as Adagrad and Adam are crucial for achieving state-of-the-art performance in machine translation and language modeling. However, these methods maintain...

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📝 The paper "GANPaint Studio - Semantic Photo Manipulation with a Generative Image Prior" and its online demo are available here:
http://ganpaint.io/

🙏 We would…

custom cuda kernel for {2, 3}d relative attention with pytorch wrapper - GitHub - Separius/CudaRelativeAttention: custom cuda kernel for {2, 3}d relative attention with pytorch wrapper

DeepFaceLab is the leading software for creating deepfakes. - iperov/DeepFaceLab

See how a modern neural network auto-completes your text

Generative Flow based Sequence-to-Sequence Toolkit written in Python. - XuezheMax/flowseq

A plausible definition of "reasoning" could be "algebraically manipulating previously acquired knowledge in order to answer a new question". This definition covers first-order logical inference or...

Machine Learning is a field of computer science concerned with developing systems that can learn from data.

Like statistics and linear algebra, probability is another foundational field that supports machine learning. Probability is a field of mathematics…