Fully body visual self-modeling of robot morphologies
Internal computational models of physical bodies are fundamental to the ability of robots and
animals alike to plan and control their actions. These “self-models” allow robots to consider …
animals alike to plan and control their actions. These “self-models” allow robots to consider …
Variational autoencoder for design of synthetic viral vector serotypes
Recent, rapid advances in deep generative models for protein design have focused on small
proteins with lots of data. Such models perform poorly on large proteins with limited natural …
proteins with lots of data. Such models perform poorly on large proteins with limited natural …
MIST-CF: Chemical formula inference from tandem mass spectra
Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step
toward structurally elucidating unknown metabolites. While great strides have been made …
toward structurally elucidating unknown metabolites. While great strides have been made …
Universal checkpointing: Efficient and flexible checkpointing for large scale distributed training
X Lian, SA Jacobs, L Kurilenko, M Tanaka… - arXiv preprint arXiv …, 2024 - arxiv.org
Existing checkpointing approaches seem ill-suited for distributed training even though
hardware limitations make model parallelism, ie, sharding model state across multiple …
hardware limitations make model parallelism, ie, sharding model state across multiple …
Deep Video Codec Control for Vision Models
Standardized lossy video coding is at the core of almost all real-world video processing
pipelines. Rate control is used to enable standard codecs to adapt to different network …
pipelines. Rate control is used to enable standard codecs to adapt to different network …
[HTML][HTML] Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states
Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated,
and selectively sensitive to immune checkpoint inhibition (ICI). However, the joint tumor …
and selectively sensitive to immune checkpoint inhibition (ICI). However, the joint tumor …
Deepvol: Volatility forecasting from high-frequency data with dilated causal convolutions
F Moreno-Pino, S Zohren - Quantitative Finance, 2024 - Taylor & Francis
Volatility forecasts play a central role among equity risk measures. Besides traditional
statistical models, modern forecasting techniques based on machine learning can be …
statistical models, modern forecasting techniques based on machine learning can be …
Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology
We introduce a proof of concept to parametrise the unresolved subgrid scale of sea-ice
dynamics with deep learning techniques. Instead of parametrising single processes, a single …
dynamics with deep learning techniques. Instead of parametrising single processes, a single …
[HTML][HTML] Towards multi-view consistency in neural ray fields using parametric medial surfaces
PB Sundt, T Theoharis - Computers & Graphics, 2024 - Elsevier
Deep learning methods are revolutionizing the solutions to visual computing problems, such
as shape retrieval and generative shape modeling, but require novel shape representations …
as shape retrieval and generative shape modeling, but require novel shape representations …
Transfer learning based on atomic feature extraction for the prediction of experimental 13 C chemical shifts
Forecasting experimental chemical shifts of organic compounds is a long-standing
challenge in organic chemistry. Recent advances in machine learning (ML) have led to …
challenge in organic chemistry. Recent advances in machine learning (ML) have led to …