C++

tags: Programming languages, Coding

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3-SAT
Abelian sandpile model
Abstraction and Reasoning Corpus
Adaptive Computation Time
Adversarial examples
Alan Turing
Algorithm
Algorithmic Information theory
Algorithmic probability
ALife 2020
ALife Conference
Alternative learning mechanisms
Amorphous computing
Applied maths
Art with Cellular Automata
Article: Open-endedness: The last grand challenge you’ve never heard of
Article: The Cartoon Picture of Magnets That Has Transformed Science
Article: The End of the RNA World Is Near, Biochemists Argue
Article: Uncertain times
Article: What Is an Individual? Biology Seeks Clues in Information Theory.
Article: Why Sex? Biologists Find New Explanations
Artificial Intelligence
Artificial intelligence test
Artificial life
Assembly theory
Attention
Attractor networks
Autoencoders
Automated discovery in complex systems
Automated theorem proving
Avida
Backward RNN
Benford's law
Berry's paradox
Boltzmann brain
Bongard problems
Boolean networks
Byte-pair encoding
C++
Causal inference
Cellular automata
Cellular automata as convolutional neural networks
Cellular automata as recurrent neural networks
Cellular automata as regular languages
Cellular neural networks
Chaos
Chaos computing
Chemical reaction network
Chinese room experiment
Christopher Langton
Church-Turing thesis
Climate
CMA-ES
Coding
Combinatorics
Combinatory logic
Compilation
Complex Systems
Complexity
Complexity metrics
Complexity of cellular automata
Compressed sensing
Compression
Computability theory
Computer science
Computer security
Computer vision
Computing in cellular automata
Continual learning
Conway's Game of Life
CPPN
Crosshatch automata
Data representation
Decentralization
Differential equations
Diffusion limited aggregation
Dirichlet energy
Distillation
Dynamical systems
Echo-state networks
Economic liberalism
Economics
Edge detection
Effective measure complexity
Elementary cellular automata
ELisp
Emacs
Emergence
Emergence in artificial life
Entropy
Epistasis
Epsilon machines
Evaluating NLP
Evolution
Fast Marching method
Federated learning
Finite state machines
Fractional calculus
Functional programming
Gaussian Processes
Generalization in Machine learning
Generative adversarial networks
Generative modelling
Genetic algorithms
Gradient descent
Gradient descent for wide two-layer neural networks – I : Global convergence
Gradient flow
Graham scan
Graph cellular automata
Graph convolutional networks
Graph neural networks
Graphs
Gödel's theorem
Hadamard product
Halting probability
Halting problem
Hash functions
Haskell
Haskell Curry
Hilbert curve indexing
Homomorphic encryption
Hopfield Networks
Hyperbolic geometry
Illegal numbers
Image processing
Implicit neural representations
Ising model
Java
Javascript
Jevons paradox
John Conway
Kaya identity
Kenneth Stanley
Kerberos
Kernel Methods
Knuth-Morris-Pratt string-searching algorithm
Kolmogorov complexity
Konrad Zuse
Kullback-leibler divergence
Lambda calculus
Langton's loop
Language modeling
Lempel-Ziv-Welch algorithm
Lenia
Life
Lisp
Locality-Sensitive Hashing
Logic
Logical depth
Machine learning
Make
MAP-Elites
Mathematics
Matrix factorization
Mean field theory of neural networks (talk)
Melanie Mitchell
Meta-learning
Minimum description length
Monero
Moore-Penrose inverse
Morphogenesis
Network authentication
Network programming
Networking
Neural architecture search
Neural cellular automata and implicit representations
Neural network pruning
Neural network training
Neural networks
Neural networks as dynamical systems
Neural tangent kernel
Neuroscience
NK model
NLP
Noise
Note-taking
Notes
Notes on: A Computer Scientist's View of Life, the Universe, and Everything by Schmidhuber, J. (1999)
Notes on: A model of urban evolution based on innovation diffusion by Raimbault, J. (2020)
Notes on: A new structurally dissolvable self-reproducing loop evolving in a simple cellular automata space by Sayama, H. (1999)
Notes on: Adapting to Unseen Environments through Explicit Representation of Context by Tutum, C., & Miikkulainen, R. (2020)
Notes on: AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence by Clune, J. (2019)
Notes on: An Integrated Perspective on the Constitutive and Interactive Dimensions of Autonomy by Beer, R. D. (2020)
Notes on: Cellular automata as convolutional neural networks by Gilpin, W. (2018)
Notes on: Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data by Bender, E. M., & Koller, A. (2020)
Notes on: Combinatory Chemistry: Towards a Simple Model of Emergent Evolution by Kruszewski, G., & Mikolov, T. (2020)
Notes on: Complexity and evolution: What everybody knows by McShea, D. W. (1991)
Notes on: Curiosity-Driven Exploration by Self-Supervised Prediction by Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017)
Notes on: Developmental mappings and phenotypic complexity by Lehre, P. K., & Haddow, P. C. (2003)
Notes on: Diversity preservation in minimal criterion coevolution through resource limitation by Brant, J. C., & Stanley, K. O. (2020)
Notes on: Drinking from a Firehose: Continual Learning with Web-scale Natural Language by Hu, H., Sener, O., Sha, F., & Koltun, V. (2020)
Notes on: Efficient Neural Architecture Search via Parameter Sharing by Pham, H., Guan, M. Y., Zoph, B., Le, Q. V., & Dean, J. (2018)
Notes on: Emergence in artificial life by Gershenson, C. (2021)
Notes on: Evolution in asynchronous cellular automata by Nehaniv, C. L. (2003)
Notes on: Evolved Open-Endedness, Not Open-Ended Evolution by Pattee, H. H., & Sayama, H. (2019)
Notes on: Evolving a self-repairing, self-regulating, French flag organism by Miller, J. F. (2004)
Notes on: Evolving Neural Networks through Augmenting Topologies by Stanley, K. O., & Miikkulainen, R. (2002)
Notes on: Fast and stable MAP-Elites in noisy domains using deep grids by Flageat, M., & Cully, A. (2020)
Notes on: Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems by Adams, A., Zenil, H., Davies, P. C. W., & Walker, S. I. (2017)
Notes on: Generalization over different cellular automata rules learned by a deep feed-forward neural network by Aach, M., Goebbert, J. H., & Jitsev, J. (2021)
Notes on: Growing Neural Cellular Automata by Mordvintsev, A., Randazzo, E., Niklasson, E., & Levin, M. (2020)
Notes on: Hopfield Networks is All You Need by Ramsauer, H., Schäfl, B., Lehner, J., Seidl, P., Widrich, M., Gruber, L., Holzleitner, M., … (2020)
Notes on: Information-Theoretic Probing with Minimum Description Length by Voita, E., & Titov, I. (2020)
Notes on: Intelligence without representation by Brooks, R. A. (1991)
Notes on: Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems by Reinke, C., Etcheverry, M., & Oudeyer, P. (2020)
Notes on: Learned Initializations for Optimizing Coordinate-Based Neural Representations by Tancik, M., Mildenhall, B., Wang, T., Schmidt, D., Srinivasan, P. P., Barron, J. T., & Ng, R. (2021)
Notes on: Learning Transferable Architectures for Scalable Image Recognition by Zoph, B., Vasudevan, V., Shlens, J., & Le, Q. V. (2018)
Notes on: Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks by Voelker, A., Kajić, I., & Eliasmith, C. (2019)
Notes on: Modeling systems with internal state using evolino by Wierstra, D., Gomez, F. J., & Schmidhuber, J. (2005)
Notes on: Molecule Attention Transformer by Maziarka, Ł., Danel, T., Mucha, S., Rataj, K., Tabor, J., & Jastrzębski, S. (2020)
Notes on: More Is Different by Anderson, P. W. (1972)
Notes on: Network Deconvolution by Ye, C., Evanusa, M., He, H., Mitrokhin, A., Goldstein, T., Yorke, J. A., Fermuller, Cornelia, … (2020)
Notes on: Neural Architecture Search with Reinforcement Learning by Zoph, B., & Le, Q. V. (2017)
Notes on: Neural Circuit Policies Enabling Auditable Autonomy by Lechner, M., Hasani, R., Amini, A., Henzinger, T. A., Rus, D., & Grosu, R. (2020)
Notes on: Neuroevolution: from architectures to learning by Floreano, D., Dürr, P., & Mattiussi, C. (2008)
Notes on: Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention by Xiong, Y., Zeng, Z., Chakraborty, R., Tan, M., Fung, G., Li, Y., & Singh, V. (2021)
Notes on: On Adversarial Mixup Resynthesis by Beckham, C., Honari, S., Verma, V., Lamb, A., Ghadiri, F., Hjelm, R. D., Bengio, Y., … (2019)
Notes on: On the expressive power of programming languages by Felleisen, M. (1991)
Notes on: PCGRL: Procedural Content Generation via Reinforcement Learning by Khalifa, A., Bontrager, P., Earle, S., & Togelius, J. (2020)
Notes on: POET: open-ended coevolution of environments and their optimized solutions by Wang, R., Lehman, J., Clune, J., & Stanley, K. O. (2019)
Notes on: Pretrained Transformers as Universal Computation Engines by Lu, K., Grover, A., Abbeel, P., & Mordatch, I. (2021)
Notes on: Regenerating Soft Robots through Neural Cellular Automata by Horibe, K., Walker, K., & Risi, S. (2021)
Notes on: Reservoir Computing in Artificial Spin Ice by Jensen, J. H., & Tufte, G. (2020)
Notes on: Reservoir Computing meets Recurrent Kernels and Structured Transforms by Dong, J., Ohana, R., Rafayelyan, M., & Krzakala, F. (2020)
Notes on: Resilient Life: An Exploration of Perturbed Autopoietic Patterns in Conway's Game of Life by Cika, A., Cohen, E., Kruszewski, G., Seet, L., Steinmann, P., & Yin, W. (2020)
Notes on: Safe Reinforcement Learning through Meta-learned Instincts by Grbic, D., & Risi, S. (2020)
Notes on: Scaling down Deep Learning by Greydanus, S. (2020)
Notes on: Seeking open-ended evolution in Swarm Chemistry by Sayama, H. (2011)
Notes on: Spontaneous fine-tuning to environment in many-species chemical reaction networks by Horowitz, J. M., & England, J. L. (2017)
Notes on: The Architecture of Complexity by Simon, H. A. (1962)
Notes on: The geometry of integration in text classification RNNs by Aitken, K., Ramasesh, V. V., Garg, A., Cao, Y., Sussillo, D., & Maheswaranathan, N. (2020)
Notes on: The information theory of individuality by Krakauer, D., Bertschinger, N., Olbrich, E., Flack, J. C., & Ay, N. (2020)
Notes on: Thinking Like Transformers by Weiss, G., Goldberg, Y., & Yahav, E. (2021)
Notes on: Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention by Katharopoulos, A., Vyas, A., Pappas, N., & Fleuret, F. (2020)
Notes on: Transition phenomena in cellular automata rule space by Li, W., Packard, N. H., & Langton, C. G. (1990)
Novelty search
Nyström method
Online privacy
Ontogeny recapitulates phylogeny
Open-ended Evolution
Optimal control
Optimization
Org-mode
Org-roam
Physics
Picbreeder
Poincaré recurrence time
Privacy-preserving machine learning
Program synthesis
Programming languages
Public key encryption
Python
Quality diversity
Rainbow tables
Raven's progressive matrices
Reaction-diffusion
Recurrent neural networks
Reductionism
Regular expressions
Reinforcement learning
Reservoir computing
Reversible cellular automata
Rice’s theorem
Richard Sutton
Ring signatures
RNA-world
Robotics
Ruby
Rust
Santa Fe Institute
Scala
Schmidhuber on Consciousness
Sed utility
Self-organization
Self-replication
Self-supervised learning
Simpson's paradox
SIR model
Softmax
Statistical complexity
Statistical physics
Style transfer
Supervised learning
Surprisingly Turing-Complete
Symmetric encryption
System of linear equations
Talk: Alife 2020 keynote Lee Cronin - A Top Down Chemically Embodied Artificial Life Computation
Talk: Alife 2020 keynote Luis Zaman - New Frontiers in Alife: What was old is new again
Talk: Alife 2020 keynote Michael Levin - Robot Cancer
Talk: Alife 2020 keynote Sara Walker - The Natural History of Information
Talk: Artificial Intelligence: A Guide for Thinking Humans
Talk: Differentiation of black-box combinatorial solvers
Talk: The Importance of Open-Endedness in AI and Machine Learning
Text classification
The Bitter Lesson
The Lottery ticket hypothesis
The Simulated reality hypothesis
Theory of computation
Tierra
Transfer learning
Transformers
Turing completeness of cellular automata
Turing degree
Turing Machine
Turing test
Turing-completeness
Unconventional computing
Unker non-linear writing system
Unsupervised learning
Urban science
Variational autoencoders
Von Neumann's self-reproducing CA
Wavelets
Why programming is a good medium for expressing poorly understood and sloppily-formulated ideas
Wirth's law
Word vectors
Zuse's thesis

Last changed 09/07/2020 | authored by Hugo Cisneros

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