Канал: London Machine Learning Meetup

Ziming Liu | KAN: Kolmogorov-Arnold Networks

Ziming Liu | KAN: Kolmogorov-Arnold Networks

Meng Fang | Large Language Models Are Neurosymbolic Reasoners

Meng Fang | Large Language Models Are Neurosymbolic Reasoners

Yuxiong Wang | Bridging Generative & Discriminative Learning in the Open World

Yuxiong Wang | Bridging Generative & Discriminative Learning in the Open World

Brenden M. Lake | Addressing Two Classic Debates in Cognitive Science with Deep Learning

Brenden M. Lake | Addressing Two Classic Debates in Cognitive Science with Deep Learning

Yuandong Tian | Efficient Inference of LLMs with Long Context Support

Yuandong Tian | Efficient Inference of LLMs with Long Context Support

Baptiste Rozière | Code Llama: Open Foundation Models for Code

Baptiste Rozière | Code Llama: Open Foundation Models for Code

Jean Kaddour & Joshua Harris | Challenges and Applications of Large Language Models

Jean Kaddour & Joshua Harris | Challenges and Applications of Large Language Models

Ofir Press | Complementing Scale: Novel Guidance Methods for Improving Language Models

Ofir Press | Complementing Scale: Novel Guidance Methods for Improving Language Models

Joon Sung Park | Generative Agents: Interactive Simulacra of Human Behavior

Joon Sung Park | Generative Agents: Interactive Simulacra of Human Behavior

Tim Dettmers | QLoRA: Efficient Finetuning of Quantized Large Language Models

Tim Dettmers | QLoRA: Efficient Finetuning of Quantized Large Language Models

Meta AI | Language Models Can Teach Themselves to Use Tools

Meta AI | Language Models Can Teach Themselves to Use Tools

Shikun Liu | Vision-Language Reasoning with Multi-Modal Experts

Shikun Liu | Vision-Language Reasoning with Multi-Modal Experts

Lukas Lange | SwitchPrompt: Learning Domain-Specific Gated Soft Prompts

Lukas Lange | SwitchPrompt: Learning Domain-Specific Gated Soft Prompts

Jing Yu Koh | Grounding Language Models to Images for Multimodal Generation

Jing Yu Koh | Grounding Language Models to Images for Multimodal Generation

Meta AI | Human-level Play in Diplomacy Through Language Models & Reasoning

Meta AI | Human-level Play in Diplomacy Through Language Models & Reasoning

Andrew Lampinen | Language models show human-like content effects on reasoning

Andrew Lampinen | Language models show human-like content effects on reasoning

Lucas Beyer | Learning General Visual Representations

Lucas Beyer | Learning General Visual Representations

Gwanghyun Kim | DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation

Gwanghyun Kim | DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation

David Ha | Collective Intelligence for Deep Learning: A Survey of Recent Developments

David Ha | Collective Intelligence for Deep Learning: A Survey of Recent Developments

Stéphane d'Ascoli | Solving Symbolic Regression with Transformers

Stéphane d'Ascoli | Solving Symbolic Regression with Transformers

Ting Chen | Pix2Seq: A New Language Interface for Object Detection and Beyond

Ting Chen | Pix2Seq: A New Language Interface for Object Detection and Beyond

Drew Jaegle | Perceivers: Towards General-Purpose Neural Network Architectures

Drew Jaegle | Perceivers: Towards General-Purpose Neural Network Architectures

Martha White | Advances in Value Estimation in Reinforcement Learning

Martha White | Advances in Value Estimation in Reinforcement Learning

Alexey Bochkovskiy | YOLOv4 and Dense Prediction Transformers

Alexey Bochkovskiy | YOLOv4 and Dense Prediction Transformers

Anna Rogers | BERTology nuggets: what we have learned about how BERT works

Anna Rogers | BERTology nuggets: what we have learned about how BERT works

Anees Kazi | Graph Convolutional Network for Disease Prediction with Imbalanced Data

Anees Kazi | Graph Convolutional Network for Disease Prediction with Imbalanced Data

Thomas Kipf | Relational Structure Discovery

Thomas Kipf | Relational Structure Discovery

Anima Anandkumar | AI4Science: A Revolution in the Making

Anima Anandkumar | AI4Science: A Revolution in the Making

Christian Szegedy | The Inverse Mindset of Machine Learning

Christian Szegedy | The Inverse Mindset of Machine Learning

Frank Willett | High-performance brain-to-text communication via handwriting

Frank Willett | High-performance brain-to-text communication via handwriting

Omer Levy | Natural Language Processing without Big Labeled Data

Omer Levy | Natural Language Processing without Big Labeled Data

Xavier Bresson | The Transformer Network for the Traveling Salesman Problem

Xavier Bresson | The Transformer Network for the Traveling Salesman Problem

Noam Brown | AI for Imperfect-Information Games: Poker and Beyond

Noam Brown | AI for Imperfect-Information Games: Poker and Beyond

Mike Lewis | Beyond BERT: Representation Learning for Natural Language at Scale

Mike Lewis | Beyond BERT: Representation Learning for Natural Language at Scale

Irwan Bello | LambdaNetworks and Recent Developments in Computer Vision

Irwan Bello | LambdaNetworks and Recent Developments in Computer Vision

Mingxing Tan | AutoML for Efficient Vision Learning

Mingxing Tan | AutoML for Efficient Vision Learning

Manzil Zaheer | Big Bird: Transformers for Longer Sequences

Manzil Zaheer | Big Bird: Transformers for Longer Sequences

Jakob Foerster | Zero-Shot (Human-AI) Coordination (in Hanabi) and Ridge Rider

Jakob Foerster | Zero-Shot (Human-AI) Coordination (in Hanabi) and Ridge Rider

Sasha Rush | Beyond Softmax: Deep Probabilistic Structure in NLP

Sasha Rush | Beyond Softmax: Deep Probabilistic Structure in NLP

Sindy Löwe: Putting An End to End-to-End

Sindy Löwe: Putting An End to End-to-End

Brenden Lake | Compositional generalization in minds and machines

Brenden Lake | Compositional generalization in minds and machines

Nick Cheney - Learning to Continually Learn

Nick Cheney - Learning to Continually Learn

Max Welling - Make VAEs Great Again: Unifying VAEs and Flows

Max Welling - Make VAEs Great Again: Unifying VAEs and Flows

Sebastian Ruder: Cross-lingual Transfer Learning

Sebastian Ruder: Cross-lingual Transfer Learning

Charles Blundell - Agent57: Outperforming the Atari Human Benchmark

Charles Blundell - Agent57: Outperforming the Atari Human Benchmark

David Silver - Deep Reinforcement Learning from AlphaGo to AlphaStar

David Silver - Deep Reinforcement Learning from AlphaGo to AlphaStar

Ricardo Silva: Machine Learning for Building Different Roads to Causal Structure

Ricardo Silva: Machine Learning for Building Different Roads to Causal Structure

Robin Manhaeve - DeepProbLog: Neural Probabilistic Logic Programming

Robin Manhaeve - DeepProbLog: Neural Probabilistic Logic Programming

Vincent Spruyt: Loc2Vec: Self-supervised metric learning through triplet-loss

Vincent Spruyt: Loc2Vec: Self-supervised metric learning through triplet-loss

Edward Grefenstette: Teaching Artificial Agents to Understand Language by Modelling Reward

Edward Grefenstette: Teaching Artificial Agents to Understand Language by Modelling Reward

Wang-Zhou Dai: Bridging Machine Learning and Logical Reasoning by Abductive Learning

Wang-Zhou Dai: Bridging Machine Learning and Logical Reasoning by Abductive Learning

Tom Rainforth: Amortized Monte Carlo Integration

Tom Rainforth: Amortized Monte Carlo Integration

Matthew Crosby: The Animal-AI Olympics

Matthew Crosby: The Animal-AI Olympics

Benjamin Schrauwen: Deep learning for 3D printing manufacturing

Benjamin Schrauwen: Deep learning for 3D printing manufacturing

Anita Faul: Towards Explainable AI

Anita Faul: Towards Explainable AI

Chris Holmes: Bayesian nonparametric ML through randomized loss functions & posterior bootstraps

Chris Holmes: Bayesian nonparametric ML through randomized loss functions & posterior bootstraps

Tim Rocktäschel: Learning with Explanations

Tim Rocktäschel: Learning with Explanations

Benjamin Bloem-Reddy: Probabilistic Symmetry and Invariant Neural Networks

Benjamin Bloem-Reddy: Probabilistic Symmetry and Invariant Neural Networks

Sander Dieleman: Generating music in the raw audio domain

Sander Dieleman: Generating music in the raw audio domain

Thomas Lukasiewicz: Learning & Reasoning in Artificial Intelligence

Thomas Lukasiewicz: Learning & Reasoning in Artificial Intelligence

Dino Sejdinovic: Kernel Embeddings, Meta Learning & Distributional Transfer

Dino Sejdinovic: Kernel Embeddings, Meta Learning & Distributional Transfer

Ryutaro Tanno: Neural Networks and Decision Trees

Ryutaro Tanno: Neural Networks and Decision Trees

Zbigniew Wojna: Architectures for big scale 2D imagery

Zbigniew Wojna: Architectures for big scale 2D imagery

Tarek Besold: Trees, Oracles, Explanations

Tarek Besold: Trees, Oracles, Explanations

Rishabh Mehrotra: Recommendations in a Marketplace (part 2)

Rishabh Mehrotra: Recommendations in a Marketplace (part 2)

Rishabh Mehrotra: Recommendations in a Marketplace (part 1)

Rishabh Mehrotra: Recommendations in a Marketplace (part 1)

Sam Ritter: Meta-Learning to Make Smart Inferences from Small Data

Sam Ritter: Meta-Learning to Make Smart Inferences from Small Data

Aldo Faisal: Beyond pattern recognition for human-in-the-Loop: the AI clinician

Aldo Faisal: Beyond pattern recognition for human-in-the-Loop: the AI clinician

Shakir Mohamed: Searching for the Principles of Reasoning and Intelligence

Shakir Mohamed: Searching for the Principles of Reasoning and Intelligence

Vaishak Belle: Towards Interpretable and Responsible AI in Structured Worlds

Vaishak Belle: Towards Interpretable and Responsible AI in Structured Worlds

Loic Matthey: Learning and leveraging disentangled representations for RL

Loic Matthey: Learning and leveraging disentangled representations for RL

Piotr Mirowski: Learning to Navigate

Piotr Mirowski: Learning to Navigate

R. Bunel & L. Berrada: Optimisation & Deep learning: training and verifying deep neural networks

R. Bunel & L. Berrada: Optimisation & Deep learning: training and verifying deep neural networks

Ronnie Clark: Recurrent Neural Models for Machine Perception

Ronnie Clark: Recurrent Neural Models for Machine Perception

Jeremy Reffin: Some Theoretical Underpinnings for Language Processing

Jeremy Reffin: Some Theoretical Underpinnings for Language Processing

Xiaowen Dong: Learning graphs from data: A signal processing perspective

Xiaowen Dong: Learning graphs from data: A signal processing perspective

Daniel Worrall: Understanding and Generalising the Convolution

Daniel Worrall: Understanding and Generalising the Convolution

Michael Betancourt: Scalable Bayesian Inference with Hamiltonian Monte Carlo

Michael Betancourt: Scalable Bayesian Inference with Hamiltonian Monte Carlo

Google's Deepmind - Nal Kalchbrenner - a general rule for generative models

Google's Deepmind - Nal Kalchbrenner - a general rule for generative models

From Facebook AI research - Soumith Chintala - Adversarial Networks

From Facebook AI research - Soumith Chintala - Adversarial Networks

Machine Learning in Robotics - Imitation Learning for Soft Robots - Matthew Howard

Machine Learning in Robotics - Imitation Learning for Soft Robots - Matthew Howard

Machine Learning in Robotics - Autonomy Based on Experience - Ingmar Posner

Machine Learning in Robotics - Autonomy Based on Experience - Ingmar Posner