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Found 6 papers, 3 papers with code
Nodule detection and generation on chest X-rays: NODE21 Challenge
To address this, we organized a public research challenge, NODE21, aimed at the detection and generation of lung nodules in chest X-rays.
How to Train Neural Field Representations: A Comprehensive Study and Benchmark
In this work, we propose $\verb|fit-a-nef|$, a JAX-based library that leverages parallelization to enable fast optimization of large-scale NeF datasets, resulting in a significant speed-up.
Neural Modulation Fields for Conditional Cone Beam Neural Tomography
Conventional Computed Tomography (CT) methods require large numbers of noise-free projections for accurate density reconstructions, limiting their applicability to the more complex class of Cone Beam Geometry CT (CBCT) reconstruction.
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation.
Inductive Biases for Object-Centric Representations in the Presence of Complex Textures
Understanding which inductive biases could be helpful for the unsupervised learning of object-centric representations of natural scenes is challenging.
Generalization and Robustness Implications in Object-Centric Learning
The idea behind object-centric representation learning is that natural scenes can better be modeled as compositions of objects and their relations as opposed to distributed representations.
