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09/07/2023
Conformal Autoregressive Generation: Beam Search with Coverage Guarantees
We introduce two new extensions to the beam search algorithm based on co...
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05/31/2023
Adaptive Conformal Regression with Jackknife+ Rescaled Scores
Conformal regression provides prediction intervals with global coverage ...
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02/22/2023
Aligned Diffusion Schrödinger Bridges
Diffusion Schrödinger bridges (DSB) have recently emerged as a powerful ...
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08/29/2022
Attention-based Interpretable Regression of Gene Expression in Histology
Interpretability of deep learning is widely used to evaluate the reliabi...
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07/26/2022
Is Attention Interpretation? A Quantitative Assessment On Sets
The debate around the interpretability of attention mechanisms is center...
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06/18/2021
It's FLAN time! Summing feature-wise latent representations for interpretability
Interpretability has become a necessary feature for machine learning mod...
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12/05/2020
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks
Less than 1 annotated. Natural Language Processing (NLP) community has r...
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07/15/2020
Learning Invariances for Interpretability using Supervised VAE
We propose to learn model invariances as a means of interpreting a model...
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07/15/2020
On quantitative aspects of model interpretability
Despite the growing body of work in interpretable machine learning, it r...
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05/27/2020
PaccMann^RL on SARS-CoV-2: Designing antiviral candidates with conditional generative models
With the fast development of COVID-19 into a global pandemic, scientists...
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05/27/2020
Targeted design of antiviral compounds against SARS-CoV-2 with conditional generative models
With the fast development of COVID-19 into a global pandemic, scientists...
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09/30/2019
MonoNet: Towards Interpretable Models by Learning Monotonic Features
Being able to interpret, or explain, the predictions made by a machine l...
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04/25/2019
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders
In line with recent advances in neural drug design and sensitivity predi...
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04/18/2019
edGNN: a Simple and Powerful GNN for Directed Labeled Graphs
The ability of a graph neural network (GNN) to leverage both the graph t...
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11/22/2018
Inference of the three-dimensional chromatin structure and its temporal behavior
Understanding the three-dimensional (3D) structure of the genome is esse...
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11/16/2018
PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks
We present a novel approach for the prediction of anticancer compound se...
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08/18/2018
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer
We present the Network-based Biased Tree Ensembles (NetBiTE) method for ...
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03/29/2018