Measuring Consciousness as Integrated Information. - Giulio Tononi; David Balduzzi (AAAI Fall Symposium: AI and Consciousness, 2007)

Integrated Information in Discrete Dynamical Systems: Motivation and Theoretical Framework. - David Balduzzi; Giulio Tononi (PLoS Comput. Biol., 2008)

Qualia: The Geometry of Integrated Information. - David Balduzzi; Giulio Tononi (PLoS Comput. Biol., 2009)

Falsification and Future Performance. - David Balduzzi (Algorithmic Probability and Friends, 2011)

Detecting emergent processes in cellular automata with excess information. - David Balduzzi (ECAL, 2011)

Estimating integrated information with TMS pulses during wakefulness, sleep, and under anesthesia. - David Balduzzi (EMBC, 2011)

Uncovering the Temporal Dynamics of Diffusion Networks. - Manuel Gomez-Rodriguez; David Balduzzi; Bernhard Schölkopf (ICML, 2011)

On the information-theoretic structure of distributed measurements - David Balduzzi (DCM, 2011)

Information, learning and falsification - David Balduzzi (CoRR, 2011)

Towards a learning-theoretic analysis of spike-timing dependent plasticity. - David Balduzzi; Michel Besserve (NIPS, 2012)

A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function. - Pedro A. Ortega; Jordi Grau-Moya; Tim Genewein; David Balduzzi; Daniel A. Braun 001 (NIPS, 2012)

Regulating the information in spikes: a useful bias - David Balduzzi (CoRR, 2012)

Domain Generalization via Invariant Feature Representation. - Krikamol Muandet; David Balduzzi; Bernhard Schölkopf (ICML (1), 2013)

Correlated random features for fast semi-supervised learning. - Brian McWilliams; David Balduzzi; Joachim M. Buhmann (NIPS, 2013)

Metabolic Cost as an Organizing Principle for Cooperative Learning. - David Balduzzi; Pedro A. Ortega; Michel Besserve (Adv. Complex Syst., 2013)

Randomized co-training: from cortical neurons to machine learning and back again. - David Balduzzi (CoRR, 2013)

What can neurons do for their brain? Communicate selectivity with bursts. - David Balduzzi; Giulio Tononi (Theory Biosci., 2013)

Cortical prediction markets. - David Balduzzi (AAMAS, 2014)

Falsifiable implies Learnable. - David Balduzzi (CoRR, 2014)

Uncovering the structure and temporal dynamics of information propagation. - Manuel Gomez-Rodriguez; Jure Leskovec; David Balduzzi; Bernhard Schölkopf (Netw. Sci., 2014)

Kickback Cuts Backprop's Red-Tape: Biologically Plausible Credit Assignment in Neural Networks. - David Balduzzi; Hastagiri Vanchinathan; Joachim M. Buhmann (AAAI, 2015)

Domain Generalization for Object Recognition with Multi-task Autoencoders. - Muhammad Ghifary; W. Bastiaan Kleijn; Mengjie Zhang 001; David Balduzzi (ICCV, 2015)

Learning the Structure of Sum-Product Networks via an SVD-based Algorithm. - Tameem Adel; David Balduzzi; Ali Ghodsi 001 (UAI, 2015)

Semantics, Representations and Grammars for Deep Learning. - David Balduzzi (CoRR, 2015)

Compatible Value Gradients for Reinforcement Learning of Continuous Deep Policies. - David Balduzzi; Muhammad Ghifary (CoRR, 2015)

Grammars for Games: A Gradient-Based, Game-Theoretic Framework for Optimization in Deep Learning. - David Balduzzi (Frontiers Robotics AI, 2015)

Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation. - Muhammad Ghifary; W. Bastiaan Kleijn; Mengjie Zhang 001; David Balduzzi; Wen Li (ECCV (4), 2016)

Strongly-Typed Recurrent Neural Networks. - David Balduzzi; Muhammad Ghifary (ICML, 2016)

Deep Online Convex Optimization with Gated Games. - David Balduzzi (CoRR, 2016)

Compliance-Aware Bandits. - Nicolás Della Penna; Mark D. Reid; David Balduzzi (CoRR, 2016)

Strongly-Typed Agents are Guaranteed to Interact Safely. - David Balduzzi (ICML, 2017)

The Shattered Gradients Problem: If resnets are the answer, then what is the question? - David Balduzzi; Marcus Frean; Lennox Leary; J. P. Lewis 001; Kurt Wan-Duo Ma; Brian McWilliams (ICML, 2017)

Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks. - David Balduzzi; Brian McWilliams; Tony Butler-Yeoman (ICML, 2017)

Back To RGB: Deep articulated hand pose estimation from a single camera image. - Kurt Wan-Duo Ma; J. P. Lewis 001; Marcus Frean; David Balduzzi (IVCNZ, 2017)

Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization. - Muhammad Ghifary; David Balduzzi; W. Bastiaan Kleijn; Mengjie Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

The Mechanics of n-Player Differentiable Games. - David Balduzzi; Sébastien Racanière; James Martens; Jakob N. Foerster; Karl Tuyls; Thore Graepel (ICML, 2018)

Re-evaluating evaluation. - David Balduzzi; Karl Tuyls; Julien Pérolat; Thore Graepel (NeurIPS, 2018)

Stable Opponent Shaping in Differentiable Games. - Alistair Letcher; Jakob N. Foerster; David Balduzzi; Tim Rocktäschel; Shimon Whiteson (ICLR (Poster), 2019)

Open-ended learning in symmetric zero-sum games. - David Balduzzi; Marta Garnelo; Yoram Bachrach; Wojciech Czarnecki 001; Julien Pérolat; Max Jaderberg; Thore Graepel (ICML, 2019)

LOGAN: Latent Optimisation for Generative Adversarial Networks. - Yan Wu 010; Jeff Donahue; David Balduzzi; Karen Simonyan; Timothy P. Lillicrap (CoRR, 2019)

Differentiable Game Mechanics. - Alistair Letcher; David Balduzzi; Sébastien Racanière; James Martens; Jakob N. Foerster; Karl Tuyls; Thore Graepel (J. Mach. Learn. Res., 2019)

Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games. - Edward Hughes 001; Thomas W. Anthony 001; Tom Eccles; Joel Z. Leibo; David Balduzzi; Yoram Bachrach (AAMAS, 2020)

Robust Self-organization in Games: Symmetries, Conservation Laws and Dimensionality Reduction. - Sai Ganesh Nagarajan; David Balduzzi; Georgios Piliouras (AAMAS, 2020)

Smooth markets: A basic mechanism for organizing gradient-based learners. - David Balduzzi; Wojciech M. Czarnecki; Tom Anthony 001; Ian Gemp; Edward Hughes 001; Joel Z. Leibo; Georgios Piliouras; Thore Graepel (ICLR, 2020)

From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics. - Sai Ganesh Nagarajan; David Balduzzi; Georgios Piliouras (ICML, 2020)

Real World Games Look Like Spinning Tops. - Wojciech M. Czarnecki; Gauthier Gidel; Brendan D. Tracey; Karl Tuyls; Shayegan Omidshafiei; David Balduzzi; Max Jaderberg (NeurIPS, 2020)

Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. - Gauthier Gidel; David Balduzzi; Wojciech Marian Czarnecki; Marta Garnelo; Yoram Bachrach (CoRR, 2020)

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. - Gauthier Gidel; David Balduzzi; Wojciech Czarnecki 001; Marta Garnelo; Yoram Bachrach (AISTATS, 2021)

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. - Marta Garnelo; Wojciech Marian Czarnecki; Siqi Liu 002; Dhruva Tirumala; Junhyuk Oh; Gauthier Gidel; Hado van Hasselt; David Balduzzi (AAMAS, 2021)

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. - Julien Pérolat; Rémi Munos; Jean-Baptiste Lespiau; Shayegan Omidshafiei; Mark Rowland 001; Pedro A. Ortega; Neil Burch; Thomas W. Anthony 001; David Balduzzi; Bart De Vylder; Georgios Piliouras; Marc Lanctot; et al. (ICML, 2021)

D3C: Reducing the Price of Anarchy in Multi-Agent Learning. - Ian Gemp; Kevin R. McKee; Richard Everett 001; Edgar A. Duéñez-Guzmán; Yoram Bachrach; David Balduzzi; Andrea Tacchetti (AAMAS, 2022)