I'm excited to share our newest publication: "Language over Labels": https://t.co/hoHIEFtaCx
CLIP does not transfer well to radiology images. We use contrastive language supervision with a linear probe (CLS+LP) to outperform regular fine-tuning (FT) at varying data sizes.
Bei unserem Meetup zum Thema One Shot Learning blieben einige Fragen unbeantwortet. Mai und @_SebastianBlank haben diese beantwortet: https://t.co/fGmS1KtUbC #OneShotLearning#DeepLearning
We @inovexgmbh worked with five motivated students to bring an image captioning service from whiteboard to a scalable data product.
https://t.co/eXyucSRT0Q
#computervision#nlp#deeplearning
Want to export your conda environment/requirements but don't list all dependencies but only those you directly depend on / have installed explicitly, use `--from-history`
For everyone interested in German text summarization systems, have a look at the proceedings of Swisstext 2019 (https://t.co/40v4WzmQKm) to see our (@SbstnBlank, @data_hpz) contributed system description. We used a deep neural net with multilingual BERT embeddings. #SwissText2019
Would you like to listen to @data_hpz and @SbstnBlank's talk "Querying Elasticsearch with Deep Learning to Answer Natural Language Questions" again? Head over to YouTube right now and just do it (don't let your dreams be dreams): https://t.co/VntBc5mb1J
Great to see the active research in German text summarization at @SwissTextConf. Tomorrow I‘m presenting our (@SbstnBlank @data_hpz) solution with multilingual BERT embeddings for the shared task. @inovexgmbh#SwissText2019
Looks like voice assistants and natural language queries are well represented this year @berlinbuzzwords#bbuzz. Deep Learning helps indeed @SbstnBlank @data_hpz .
Neues Format! Wir möchten mit euch die Mittagspause verbringen – inklusive Tech Talk zu einem unserer Fokusthemen sowie Pizza & Networking.
Den Anfang macht @SbstnBlank, der über "Querying Elasticsearch by Asking Questions about Movies" spricht. https://t.co/g8vY26ANaq #Karlsruhe
This is a super cool resource: Papers With Code now includes 950+ ML tasks, 500+ evaluation tables (including SOTA results) and 8500+ papers with code. Probably the largest collection of NLP tasks I've seen including 140+ tasks and 100 datasets.
https://t.co/lTAGE7LGZY