Date |
Reading |
Thu 6 Apr, 15-16 |
Pavlick (2022), "Semantic structure in deep learning". |
Thu 16 Mar, 15-16 |
Chen et al. (2021), "NeuralLog: Natural language inference with joint neural and logical reasoning.". |
Thu 2 Mar, 15-16 |
Willig et al. (2022), "Can foundation models talk causality?" |
Thu 16 Feb, 15-16 |
Cruttwell et al. (2022), "Categorical foundations of gradient-based learning." |
Thu 2 Feb, 15-16 |
Mohsin et al. (2022), "Learning to design fair and private voting rules." |
Tue 19 Jan, 15-16 |
Hasson et al. (2020), "Direct fit to nature: An evolutionary perspective on biological and artificial neural networks." |
Thu 22 Dec, 15-16 |
Xie et al. (2021), "An explanation of in-context learning as implicit Bayesian inference". |
Thu 8 Dec, 15-16 |
Vaswane et al. (2017), "Attention is all you need.". |
Thu 24 Nov, 15-16 |
Buchholz and Raidl (in press), "A falsificationist account of artificial neural networks," with first author. |
Thu 3 Nov, 15-16 |
Schwöbel and Remmers (2022), "The long arc of fairness: Formalisations and ethical discourse." |
Date |
Reading |
Mon 12 Sep, 16-17 |
Hedden (2021), "On statistical criteria of algorithmic fairness." |
Mon 8 Aug, 16-17 |
Seth (2015), "The cybernetic Bayesian brain." |
Mon 11 Jul, 16-17 |
Dreyfus (2007), "Why Heideggerian AI failed and how fixing it would require making it more Heideggerian." |
Mon 20 Jun, 16-17 |
Chollet (2019), "On the measure of intelligence." |
Mon 30 May, 16-17 |
Chauhan et al. (2020), "Automated machine learning: The new wave of machine learning." |
Mon 16 May, 16-17 |
Bowers et al. (2022), "Deep problems with neural network models of human vision." |
Mon 25 Apr, 16-17 |
Buckner (2020), "Understanding adversarial examples requires a theory of artefacts for deep learning". |
Mon 4 Apr, 16-17 |
Boge (2022), "Two dimensions of opacity and the deep learning predicament." |
Mon 14 Mar, 16-17 |
Enni and Herrie (2021), "Turning biases into hypotheses through method: A logic of scientific discovetery for machine learning." |