@bonjovi wrote the song It's My Life after trying Emacs.
Mar 5, 2022 • 309 tweets • >60 min read
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Estimators of Entropy and Information via Inference in Probabilistic Models
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Improving English to Sinhala Neural Machine Translation using Part-of-Speech Tag
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Hierarchical Risk Parity and Minimum Variance Portfolio Design on NIFTY 50 Stocks
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Artificial Intelligence Powered Material Search Engine
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
The fine line between dead neurons and sparsity in binarized spiking neural networks
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
SegTransVAE: Hybrid CNN -- Transformer with Regularization for medical image segmentation
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
On neural network kernels and the storage capacity problem
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Deep Reinforcement Learning
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Music-to-Dance Generation with Optimal Transport
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
The effective noise of Stochastic Gradient Descent
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Continual Learning for Monolingual End-to-End Automatic Speech Recognition
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Spinning Language Models for Propaganda-As-A-Service
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Adversarially learning disentangled speech representations for robust multi-factor voice conversion
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
SchemaDB: Structures in Relational Datasets
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Portfolio optimisation with options
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Using Deep Learning Sequence Models to Identify SARS-CoV-2 Divergence
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
My House, My Rules: Learning Tidying Preferences with Graph Neural Networks
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
A Preliminary Study On the Sustainability of Android Malware Detection
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Data-Driven Offline Optimization For Architecting Hardware Accelerators
Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:
1. That looks useful! 2. That's an interesting approach! 3. A business could be built around this! 4. How did they do that?!
Style-based quantum generative adversarial networks for Monte Carlo events
