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Found 10 papers, 1 papers with code
De novo protein design using geometric vector field networks
Most prior encoders rely on atom-wise features, such as angles and distances between atoms, which are not available in this context.
Stecformer: Spatio-temporal Encoding Cascaded Transformer for Multivariate Long-term Time Series Forecasting
With the development of transformer-based methods, the performance of multivariate long-term time series forecasting has been significantly improved, however, the study of spatial features extracting in transformer-based model is rare and the consistency of different prediction periods is unsatisfactory due to the large span.
Towards the Universal Defense for Query-Based Audio Adversarial Attacks
In this work, we propose a novel method to infer the adversary intent and discover audio adversarial examples based on the AEs generation process.
Towards the Transferable Audio Adversarial Attack via Ensemble Methods
In this work, we explore the potential factors that impact adversarial examples (AEs) transferability in DL-based speech recognition.
Robust Table Structure Recognition with Dynamic Queries Enhanced Detection Transformer
Unlike previous methods, we formulate table separation line prediction as a line regression problem instead of an image segmentation problem and propose a new two-stage dynamic queries enhanced DETR based separation line regression approach, named DQ-DETR, to predict separation lines from table images directly.
TSRFormer: Table Structure Recognition with Transformers
We present a new table structure recognition (TSR) approach, called TSRFormer, to robustly recognizing the structures of complex tables with geometrical distortions from various table images.
Ranked #2 on
Table Recognition
on PubTabNet
(TEDS-Struct metric)
Real-time Localized Photorealistic Video Style Transfer
We present a novel algorithm for transferring artistic styles of semantically meaningful local regions of an image onto local regions of a target video while preserving its photorealism.
Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer
Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera.
Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition
We further show that applying deep residual learning can boost the convergence speed of our novel deep recurret convolutional networks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Composing Music with Grammar Argumented Neural Networks and Note-Level Encoding
Creating aesthetically pleasing pieces of art, including music, has been a long-term goal for artificial intelligence research.
