Andrew Jesson | DeepAI

DeepAI AI Chat

Featured Co-authors

Yoshua Bengio
448 publications
Bernhard Schölkopf
271 publications
Yarin Gal
126 publications
Nathan Kallus
88 publications
Stefan Bauer
68 publications
Stan Matwin
42 publications
Uri Shalit
29 publications
Arash Mehrjou
29 publications
Nicolai Meinshausen
29 publications
Tristan Deleu
23 publications
Mohammad Havaei
22 publications

∙ 06/26/2023

BatchGFN: Generative Flow Networks for Batch Active Learning

We introduce BatchGFN – a novel approach for pool-based active learning ...

0 Shreshth A. Malik, et al. ∙

∙ 06/02/2023

ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages

In this paper, we introduce a novel method for enhancing the effectivene...

0 Andrew Jesson, et al. ∙

∙ 04/20/2023

B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding

Estimating heterogeneous treatment effects from observational data is a ...

0 Miruna Oprescu, et al. ∙

∙ 02/21/2023

Differentiable Multi-Target Causal Bayesian Experimental Design

We introduce a gradient-based approach for the problem of Bayesian optim...

0 Yashas Annadani, et al. ∙

∙ 04/21/2022

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions

Estimating the effects of continuous-valued interventions from observati...

0 Andrew Jesson, et al. ∙

∙ 03/03/2022

Interventions, Where and How? Experimental Design for Causal Models at Scale

Causal discovery from observational and interventional data is challengi...

11 Panagiotis Tigas, et al. ∙

∙ 11/03/2021

Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data

Estimating personalized treatment effects from high-dimensional observat...

13 Andrew Jesson, et al. ∙

∙ 10/28/2021

Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific

Aerosol-cloud interactions include a myriad of effects that all begin wh...

0 Andrew Jesson, et al. ∙

∙ 10/22/2021

GeneDisco: A Benchmark for Experimental Design in Drug Discovery

In vitro cellular experimentation with genetic interventions, using for ...

19 Arash Mehrjou, et al. ∙

∙ 03/08/2021

Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding

We study the problem of learning conditional average treatment effects (...

0 Andrew Jesson, et al. ∙

∙ 02/22/2021

Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression

We propose a new model that estimates uncertainty in a single forward pa...

0 Joost van Amersfoort, et al. ∙

∙ 07/01/2020

Identifying Causal Effect Inference Failure with Uncertainty-Aware Models

Recommending the best course of action for an individual is a major appl...

5 Andrew Jesson, et al. ∙

∙ 07/27/2018

CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance

We introduce CASED, a novel curriculum sampling algorithm that facilitat...

0 Andrew Jesson, et al. ∙

∙ 07/14/2018

Adversarially Learned Mixture Model

The Adversarially Learned Mixture Model (AMM) is a generative model for ...

0 Andrew Jesson, et al. ∙

∙ 06/03/2018

On the Importance of Attention in Meta-Learning for Few-Shot Text Classification

Current deep learning based text classification methods are limited by t...

0 Xiang Jiang, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world