The authors combined the deep Q network in reinforcement learning with the sentiment quantitative indicator ARBR to build a high-frequency stock trading model for the share market.
The net value of the fund is affected by performance and market, and the researchers try to quantify these effects to predict the future net value by establishing different models.
With the application of artificial intelligence in the financial field, quantitative trading is considered to be profitable.
The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses.
Ranked #1 on 3D-Aware Image Synthesis on FFHQ 256 x 256
We simulated our nanomagnet reservoir computer (NMRC) design on benchmark tasks, demonstrating NMRC's high memory content and expressibility.
This paper studies video inpainting detection, which localizes an inpainted region in a video both spatially and temporally.
The conditional generative adversarial network (cGAN) is a powerful tool of generating high-quality images, but existing approaches mostly suffer unsatisfying performance or the risk of mode collapse.
Ranked #3 on Conditional Image Generation on ImageNet 128x128
To learn the sampling policy, a Markov decision process is embedded into the search algorithm and a moving average is applied for better stability.
Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments.
In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.
For machines to achieve this capability, we propose a knowledge-enabled language representation model (K-BERT) with knowledge graphs (KGs), in which triples are injected into the sentences as domain knowledge.
Finally, through this easy-to-use specification language, we are able to build a full testing specification which leverages LLVM TableGen to automatically generate unit tests for ONNX operators with much large coverage.
Instead of sequentially distilling knowledge only from the last model, we directly leverage all previous model snapshots.
The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.
On the other hand, in addition to the conventional discriminator of GAN (i. e., to distinguish between REAL/FAKE samples), we propose a novel guider sub-network which encourages the generated sample (i. e., with novel pose) towards better satisfying the ReID loss (i. e., cross-entropy ReID loss, triplet ReID loss).
Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned.
Joint extraction of entities and relations is an important task in information extraction.
Ranked #3 on Relation Extraction on NYT-single
To integrate the features on both dimensions of the matrix, this paper explores applying 2D max pooling operation to obtain a fixed-length representation of the text.
Ranked #4 on Text Classification on TREC-6
Ranked #17 on Relation Extraction on SemEval-2010 Task 8