53 citations · 155 across the 14 of their papers we have counts for
4 papers · 1 filter
Deep Probability Estimation
Sheng Liu, Aakash Kaku, Weicheng Zhu +8
Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty. Probability-estimation models are trained…
Perturbation CheckLists for Evaluating NLG Evaluation Metrics
Ananya B. Sai, Tanay Dixit, Dev Yashpal Sheth +2
Natural Language Generation (NLG) evaluation is a multifaceted task requiring assessment of multiple desirable criteria, e.g., fluency, coherency, coverage, relevance, adequacy, ov…
Adaptive Denoising via GainTuning
Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro +3
Deep convolutional neural networks (CNNs) for image denoising are usually trained on large datasets. These models achieve the current state of the art, but they have difficulties g…
Developing and Evaluating Deep Neural Network-based Denoising for Nanoparticle TEM Images with Ultra-low Signal-to-Noise
Joshua L. Vincent, Ramon Manzorro, Sreyas Mohan +6
A deep convolutional neural network has been developed to denoise atomic-resolution TEM image datasets of nanoparticles acquired using direct electron counting detectors, for appli…