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Intrinsic and environmental factors contribute to variability in the performance of cells within a battery pack, affecting the lifespan and safety of battery systems. To solve this problem, active and passive equalization methods are proposed. ...

Diversity-promoting recommender systems with the goal of recommending diverse and relevant results to users, have received significant attention. However, current studies often face a trade-off: they either recommend highly accurate but ...

Face sketch and photo synthesis is widely applied in industry and information fields, such as entertainment business and heterogeneous face retrieval. The key challenge lies in completing a face transformation with both good visual effects and ...

Recently, denoising diffusion models have demonstrated remarkable performance among generative models in various domains. However, in the speech domain, there are limitations in complexity and controllability to apply diffusion models for time-...

• Introduce HiddenSinger, a high-quality singing voice synthesis model.
• Propose HiddenSinger-U, an unsupervised learning framework to train with unlabeled datasets.
• Audio samples are available at https://jisang93.github.io/...

Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual ...

Detecting the community structure within networks is important because it aids in the analysis of complex networks. However, the existence of diverse complex structures in the network topology can limit the topological information’s ability to ...

The challenges in multi-objective and multi-dimensional optimization design of airfoils, marked by prolonged optimization cycles and low accuracy, call for an efficient solution to expedite airfoil design. This study presents an innovative ...

• Airfoil-VAE generates diverse airfoils similar to UIUC, solving data scarcity.
• AFD-CVAE reduces error by 65% compared to PG-cWGAN.
• APD-CVAE reduces error by 99.99% compared to Airfoil-Cp-GAN.

Manually annotating fine-grained slot-value labels for task-oriented dialogue (ToD) systems is an expensive and time-consuming endeavour. This motivates research into slot-filling methods that operate with limited amounts of labelled data. ...

• A knowledge-aware audio-grounded (KA2G) generative slot-filling framework is proposed
• KA2G integrates knowledge with two tree-constrained pointer generator (TCPGen)
• 4.6% and 11.2% SLU-F1 increases achieved for rare and unseen ...

Non-B DNA structures, or flipons, are important functional elements that regulate a large spectrum of cellular programs. Experimental technologies for flipon detection are limited to the subsets that are active at the time of an experiment and ...

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• Data augmentation with diffusion models improve detection of non-B DNA structures, or flipons.
• Diffusion model outperformed WGAN and VQ-VAE models for Z-DNA and H-DNA.
• WGAN models outperform diffusion models for quadruplexes.
• ...

Transportation of samples across different domains is a central task in several machine learning problems. A sensible requirement for domain transfer tasks in computer vision and language domains is the sparsity of the transportation map, i.e., ...${}_{\mathrm{}}$${}_{\mathrm{}}$

The diffusion probabilistic model (DPM) has achieved unparalleled results in current image generation tasks, and some recent research works employed it in several computer vision tasks, such as image super-resolution, object detection, etc. ...

Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist–Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks’...

• Latent diffusion-based architecture tackles image compressive sensing challenges.
• Pre-trained generative networks model the prior information of natural images.
• Diffusion models maximize likelihood estimation in a low-dimensional ...

The intersection of art and artificial intelligence (AI) is rapidly evolving, particularly within the realm of fashion design, where AI’s potential to augment human creativity is being increasingly recognized. Despite the progress achieved through ...

Sound creators make various sound effects (SFX) depending on auditory events utilizing knowledge, techniques, and experience. These are challenging tasks for inexperienced creators. In this research, we focus on the fact that it is relatively easy for ...

Currently, generative models are showing exceptional abilities to identify and generate triplets expressed within sentences within the field of Aspect Sentiment Triplet Extraction (ASTE). Although these models are capable of recognizing terms and ...

This paper introduces a Virtual Immunohistochemistry Multiplex staining (VIMs) model designed to generate multiple immunohistochemistry (IHC) stains from a single hematoxylin and eosin (H&E) stained tissue section. IHC stains are crucial in ...

Difference Visual Question Answering (DiffVQA) introduces a new task aimed at understanding and responding to questions regarding the disparities observed between two images. Unlike traditional medical VQA tasks, DiffVQA closely mirrors the ...

The imbalanced distribution of different object categories poses a challenge for training accurate object recognition models in driving scenes. Supervised machine learning models trained on imbalanced data are biased and easily overfit the ...

• Data augmentation for driving scene object recognition using generative models.
• A systematic benchmark of generative models for lidar point clouds.
• L-GAN boosts point-based and graph-based object recognition methods effectively.

In the rapidly evolving domain of image generation, the availability of sufficient data is crucial for effective model training. However, obtaining a large dataset is often challenging. Medical imaging, industrial monitoring, and self-driving ...

• Novel Approach with DDPM and ConvNeXt-V2: Combines DDPM and ConvNeXt-V2 to enhance image diversity and quality from a single input.
• High Performance and Robustness: The model excels with a Pixel Diversity score of 0.87, LPIPS ...

A nice image-to-image translation framework is able to acquire an explicit and credible mapping relationship between the source domain and target domains while satisfying two requirements. One is simplicity, the other is extensibility over ...

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• We propose a concise but versatile generative model for image-to-image tasks.
• A novel Semantics-Appearance Spatially Adaptive Normalization is introduced.
• Semantic-aware and Appearance-aware Contrastive Losses are proposed.
• An ...