Browsing: Yannic Kilcher
Deep neural networks are large models and pruning has become an important part of ML product pipelines, making models small…
Many object detectors focus on locating the center of the object they want to find. However, this leaves them with…
Neural Architecture Search is usually prohibitively expensive in both time and resources to be useful. A search strategy has to…
Proper evaluation of text generation models, such as machine translation systems, requires expensive and slow human assessment. As these models…
Join me to solve the NeurIPS 2020 challenge on multi-agent reinforcement learning in the flatland environment. This challenge has participants…
Code migration between languages is an expensive and laborious task. To translate from one language to the other, one needs…
Text-to-speech engines are usually multi-stage pipelines that transform the signal into many intermediate representations and require supervision at each step.…
Transformers are notoriously resource-intensive because their self-attention mechanism requires a squared number of memory and computations in the length of…
Pre-training a CNN backbone for visual transfer learning has recently seen a big push into the direction of incorporating more…
Determining the stability properties of differential systems is a challenging task that involves very advanced symbolic and numeric mathematical manipulations.…