activity
20162023
most citedFacilitated machine learning for image-based fruit quality assessment

98 citations · 188 across the 14 of their papers we have counts for

collaborators

25 papers

stat.ML2023★ 2 cited

Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimation

Simon Dirmeier, Carlo Albert, Fernando Perez-Cruz

Neural likelihood estimation methods for simulation-based inference can suffer from performance degradation when the modeled data is very high-dimensional or lies along a lower-dim…

stat.ML2023★ 1 cited

Adaptive Annealed Importance Sampling with Constant Rate Progress

Shirin Goshtasbpour, Victor Cohen, Fernando Perez-Cruz

Annealed Importance Sampling (AIS) synthesizes weighted samples from an intractable distribution given its unnormalized density function. This algorithm relies on a sequence of int…

stat.ML2022

Optimization of Annealed Importance Sampling Hyperparameters

Shirin Goshtasbpour, Fernando Perez-Cruz

Annealed Importance Sampling (AIS) is a popular algorithm used to estimates the intractable marginal likelihood of deep generative models. Although AIS is guaranteed to provide unb…

cs.CV2022★ 98 cited

Facilitated machine learning for image-based fruit quality assessment

Manuel Knott, Fernando Perez-Cruz, Thijs Defraeye

Image-based machine learning models can be used to make the sorting and grading of agricultural products more efficient. In many regions, implementing such systems can be difficult…

eess.IV2022★ 4 cited

OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing

Firat Ozdemir, Berkan Lafci, Xosé Luís Deán-Ben +2

Optoacoustic (OA) imaging is based on excitation of biological tissues with nanosecond-duration laser pulses followed by subsequent detection of ultrasound waves generated via ligh…

cs.CV2022★ 6 cited

What You See is What You Classify: Black Box Attributions

Steven Stalder, Nathanaël Perraudin, Radhakrishna Achanta +2

An important step towards explaining deep image classifiers lies in the identification of image regions that contribute to individual class scores in the model's output. However, d…