Trending Research
MuJoCo: A physics engine for model-based control
To facilitate optimal control applications and in particular sampling and finite differencing, the dynamics can be evaluated for different states and controls in parallel.
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
However, like other modern SSL algorithms, FixMatch uses a pre-defined constant threshold for all classes to select unlabeled data that contribute to the training, thus failing to consider different learning status and learning difficulties of different classes.
Non-deep Networks
This begs the question -- is it possible to build high-performing "non-deep" neural networks?
Multitask Prompted Training Enables Zero-Shot Task Generalization
Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks.
SaLinA: Sequential Learning of Agents
SaLinA is a simple library that makes implementing complex sequential learning models easy, including reinforcement learning algorithms.
ADOP: Approximate Differentiable One-Pixel Point Rendering
The input are an initial estimate of the point cloud and the camera parameters.
Lenia and Expanded Universe
We report experimental extensions of Lenia, a continuous cellular automata family capable of producing lifelike self-organizing autonomous patterns.
ByteTrack: Multi-Object Tracking by Associating Every Detection Box
ifzhang/ByteTrack
•
•
arXiv 2021
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in videos.
Ranked #1 on
Multi-Object Tracking
on MOT17
(using extra training data)
Alias-Free Generative Adversarial Networks
NVlabs/stylegan3
•
•
We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner.
Ranked #1 on
Image Generation
on FFHQ-U
Resolution-robust Large Mask Inpainting with Fourier Convolutions
saic-mdal/lama
•
•
We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function.
