2022-05-17 Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shift
2022-05-12 Minimal Neural Network Models for Permutation Invariant Agents
2021-12-08 A Call to Build Models Like We Build Open-Source Software
2021-11-02 Correspondence Between Neuroevolution and Gradient Descent
2021-10-11 Chaos as an Interpretable Benchmark for Forecasting and Data-Driven Modelling
2021-10-18 Learning in High Dimension Always Amounts to Extrapolation
2021-06-16 Knowledge-Adaptation Priors
2021-04-26 Why AI is Harder Than We Think
2021-01-14 Training Learned Optimizers with Randomly Initialized Learned Optimizers
2021-01-08 Evolving Reinforcement Learning Algorithms
2020-12-06 Neural Networks (Maybe) Evolved to Make Adam the Best Optimizer
2020-12-03 Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
2020-11-06 Underspecification Presents Challenges for Credibility in Modern Machine Learning
2020-11-05 Adapting on the Fly to Test Time Distribution Shift
2020-07-11 Learning to Learn with Quantum Neural Networks via Classical Neural Networks
2020-07-06 Meta-Learning through Hebbian Plasticity in Random Networks
2020-07-00 Why and When Are Loops Useful in Genetic Programming?
2020-06-22 Learning with AMIGo: Adversarially Motivated Intrinsic Goals
2020-05-28 Language Models are Few-Shot Learners
2020-05-27 First Return Then Explore
2020-05-08 Transforming Task Representations to Allow Deep Learning Models to Perform Novel Tasks
2020-05-02 Synthesizer: Rethinking Self-Attention in Transformer Models
2020-04-20 Real World Games Look Like Spinning Tops
2020-04-19 The Cost of Training NLP Models: A Concise Overview
2020-04-16 Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars
2020-04-10 Longformer: The Long-Document Transformer
2020-04-07 Adversarial Validation Approach to Concept Drift Problem in Automated Machine Learning Systems
2020-03-18 Neuroevolution of Self-Interpretable Agents
2020-03-03 Scaling MAP-Elites to Deep Neuroevolution
2020-02-14 Deep reconstruction of strange attractors from time series
2020-02-03 Proving the Lottery Ticket Hypothesis: Pruning is All You Need
2019-12-05 Reinforcement Learning Upside Down: Don’t Predict Rewards — Just Map Them to Actions
2019-12-04 Deep Double Descent: Where Bigger Models and More Data Hurt
2019-11-19 Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
2019-11-18 Illustrated: Self-Attention
2019-11-13 Compressive Transformers for Long-Range Sequence Modelling
2019-11-05 On the Measure of Intelligence
2019-09-28 Information Closure Theory of Consciousness
2019-08-31 Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension
2019-08-21 A Critique of Pure Learning and What Artificial Neural Networks Can Learn From Animal Brains
2019-08-09 Why Open-Endedness Matters
2019-07-05 Invariant Risk Minimization
2019-06-23 Meta Reinforcement Learning
2019-06-12 Weight Agnostic Neural Networks
2019-05-28 EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
2019-05-03 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
2019-04-16 Reinforcement Learning, Fast and Slow
2019-04-05 Synchronization of Chaotic Systems and Their Machine-Learning Models
2018-12-28 Reconciling Modern Machine Learning Practice and the Bias-Variance Trade-Off
2018-12-14 How AI Training Scales
2018-11-30 Meta-Learning: Learning to Learn Fast
2018-10-27 Algorithmic Information and Incompressibility of Families of Multidimensional Networks
2018-10-10 Reinforcement Learning for Improving Agent Design
2018-09-27 One Parameter is Always Enough
2018-08-16 BlockQNN: Efficient Block-wise Neural Network Architecture Generation
2018-07-10 Universal Transformers
2018-06-06 Meta-Learning by the Baldwin Effect
2018-06-04 Playing Atari with Six Neurons
2018-05-22 Deep Learning Generalizes Because the Parameter-Function Map is Biased Towards Simple Functions
2018-05-00 Never-Ending Learning
2018-03-09 The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
2018-02-24 Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari
2018-02-05 Regularized Evolution for Image Classifier Architecture Search
2017-12-18 On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent
2017-10-12 An Algorithmic Information Theory of Consciousness
2017-10-10 High-dimensional dynamics of generalization error in neural networks
2017-07-00 Recent developments in autoconstructive evolution
2017-07-00 Minimal Criterion Coevolution: A New Approach to Open-Ended Search
2017-06-07 Are Saddles Good Enough for Deep Learning?
2017-03-06 Neural Episodic Control
2017-02-27 The Revival of the Baldwin Effect
2016-11-10 Understanding Deep Learning Requires Rethinking Generalization
2016-07-00 Evolution Evolves with Autoconstruction
2016-07-00 Simple Evolutionary Optimization Can Rival Stochastic Gradient Descent in Neural Networks
2016-06-08 Convolution by Evolution: Differentiable Pattern Producing Networks
2016-05-19 Defining and simulating open-ended novelty: requirements, guidelines, and challenges
2016-00-00 A Detailed Analysis of a PushGP Run
2015-11-09 Evolutionary Algorithms as Fitness Function Debuggers
2015-10-30 VISALOGY: Answering Visual Analogy Questions
2015-04-20 Illuminating Search Spaces by Mapping Elites
2015-04-02 Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills
2014-05-03 Evaluating Gambles using Dynamics
2013-08-20 Experiments on the Role of Deleterious Mutations as Stepping Stones in Adaptive Evolution
2013-07-10 Hyper-Heuristics: A Survey of the State of the Art
2013-06-02 The Ghost in the Quantum Turing Machine
2013-03-22 The Evolutionary Origins of Modularity
2012-10-22 The state of Computer Vision and AI: we are really, really far away
2012-09-29 Self-Delimiting Neural Networks
2012-08-21 Task-Switching Costs Promote the Evolution of Division of Labor and Shifts in Individuality
2012-01-00 The Standard Definition of Creativity
2011-08-14 Why Philosophers Should Care About Computational Complexity
2011-07-14 Improving Evolvability Through Novelty Search and Self-Adaptation
2011-06-00 Abandoning Objectives: Evolution Through the Search for Novelty Alone
2010-05-14 Open Issues in Genetic Programming
2008-08-19 Closed Timelike Curves Make Quantum and Classical Computing Equivalent
2007-12-00 The Road to Modularity
2007-08-21 Varying Environments Can Speed Up Evolution
2007-08-19 A Long-Term Evolutionary Pressure on the Amount of Noncoding DNA
2006-08-25 Stationary Algorithmic Probability
2006-07-00 Information and Closure in Systems Theory
2005-09-27 Spontaneous Evolution of Modularity and Network Motifs
2005-02-12 NP-complete Problems and Physical Reality
2005-00-00 Increasing Kolmogorov Complexity
2004-10-07 Pleiotropy as a Mechanism to Stabilize Cooperation
2002-10-15 Open-Ended Artificial Evolution
2002-04-00 A Lamarckian Approach for Neural Network Training
2002-03-00 Genetic Programming and Autoconstructive Evolution with the Push Programming Language
2001-07-19 Evolution of Digital Organisms at High Mutation Rates Leads to Survival of the Flattest
2000-00-00 Open Problems in Artificial Life
1999-09-14 Modeling Evolutionary Landscapes: Mutational Stability, Topology, and Superfunnels in Sequence Space
1999-03-00 Evolution Strategies: An Alternative Evolutionary Algorithm
1998-00-00 Reinforcement Learning with Self-Modifying Policies
1997-00-00 A Comparison of Evolutionary Activity in Artificial Evolving Systems and in the Biosphere
1994-07-00 Use of Genetic Programming for the Search of a New Learning Rule for Neural Networks
1990-06-00 Computation at the Edge of Chaos: Phase Transitions and Emergent Computation